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Database and expert systems applications . Part I : 33rd International Conference, DEXA 2022, Vienna, Austria, August 22-24, 2022, proceedings / / Christine Strauss [and four others], editors
Database and expert systems applications . Part I : 33rd International Conference, DEXA 2022, Vienna, Austria, August 22-24, 2022, proceedings / / Christine Strauss [and four others], editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer International Publishing, , [2022]
Descrizione fisica 1 online resource (469 pages)
Disciplina 005.7565
Collana Lecture Notes in Computer Science
Soggetto topico Database management
Expert systems (Computer science)
ISBN 3-031-12423-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Abstracts of Keynote Talks -- Responsible AI -- Following the Rules: From Policies to Norms -- Contents - Part I -- Contents - Part II -- Knowledge Graphs -- Jointly Learning Propagating Features on the Knowledge Graph for Movie Recommendation -- 1 Introduction -- 2 Methodology -- 2.1 Problem Formulation -- 2.2 Heterogeneous Graph Construction -- 2.3 The Proposed Framework -- 3 Experiments -- 3.1 Datasets -- 3.2 Experimental Settings -- 3.3 Experimental Results -- 3.4 Ablation Study -- 4 Conclusion -- References -- Syntax-Informed Question Answering with Heterogeneous Graph Transformer -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Graph Creation Module -- 3.2 Graph Processing and Answer Prediction -- 4 Experiments and Discussions -- 4.1 Setup -- 4.2 Evaluation -- 4.3 LingHGT, SemHGT, PragHGT: Towards Linguistics-Informed Language Models -- 5 Conclusion -- References -- Automated Process Knowledge Graph Construction from BPMN Models -- 1 Introduction -- 2 Background -- 3 Industrial Use Case -- 4 BPMN2KG Tool -- 4.1 Requirements -- 4.2 Process Knowledge Graph Construction -- 4.3 Implementation -- 5 Application Scenarios -- 6 Related Work -- 7 Conclusions -- A SPARQL Queries and Results -- References -- CAKE: A Context-Aware Knowledge Embedding Model of Knowledge Graph -- 1 Introduction -- 2 Related Work -- 3 Context-Aware Knowledge Embedding (CAKE) -- 3.1 LDA-Based Context Learning -- 3.2 HDP-Based Context Learning -- 3.3 Context-Aware Knowledge Embedding -- 4 Experimental Evaluation -- 4.1 Experiment Protocol -- 4.2 Experiment Settings -- 4.3 Experimental Results -- 5 Conclusion -- A Appendix: Optimization of CAKE -- References -- The Digitalization of Bioassays in the Open Research Knowledge Graph -- 1 Introduction -- 2 Bioassay Digitalization in the ORKG -- 3 Conclusion -- References.
Privacy-Preservation Approaches -- Privacy Issues in Smart Grid Data: From Energy Disaggregation to Disclosure Risk -- 1 Introduction -- 2 Related Work -- 2.1 Non-intrusive Load Monitoring -- 2.2 Privacy Preserving Data Publishing in Smart Grid -- 3 Proposed Method for Disclosure Risk Assessment -- 3.1 Appliance Selection -- 3.2 Seq2Seq Disaggregation Algorithm -- 3.3 Event Detection -- 3.4 Middle-Point Thresholding -- 3.5 Variance-Sensitive Thresholding -- 3.6 Activation Time Extraction -- 3.7 Disaggregation Risk -- 4 Experimental Setup -- 4.1 Datasets -- 4.2 Training and Testing Period -- 4.3 Threshold Computation -- 5 Results and Discussion -- 5.1 Inference Attack on the Same Building -- 5.2 Inference Attack on Different Buildings in the Same Dataset -- 5.3 Inference Attack on Different Buildings from Different Datasets -- 6 Conclusion -- References -- CoK: A Survey of Privacy Challenges in Relation to Data Meshes -- 1 Introduction -- 2 State-of-the-Art -- 2.1 Data Mesh Databases -- 2.2 Privacy in Mesh Networking -- 2.3 Syntactic Data Anonymisation -- 2.4 Semantic Data Anonymisation and Differential Privacy -- 2.5 Unique Column Combinations -- 2.6 High-Dimensional Data -- 2.7 Quasi-Identifier Discovery -- 3 Data Meshes -- 4 Experiments -- 5 Conclusion and Future Directions -- References -- Why- and How-Provenance in Distributed Environments -- 1 Introduction -- 2 Background and Related Work -- 2.1 Data Provenance -- 2.2 Distributed Databases -- 2.3 Related Work -- 3 Provenance in Distributed Databases -- 3.1 Architecture -- 3.2 Annotations -- 3.3 Build Provenance Information -- 4 Experimental Evaluation -- 5 Conclusions and Future Work -- References -- Provenance-Based SPARQL Query Formulation -- 1 Introduction -- 2 Model -- 3 Structural Edits -- 4 Grounding Generator -- 5 Procuring Feedback -- 6 Experiments -- 7 Related Work -- 8 Conclusion.
References -- Anonymisation of Heterogeneous Graphs with Multiple Edge Types -- 1 Introduction -- 2 K-RDF-Neighbourhood Anonymisation with Multiple Edge Types -- 3 Conclusions -- References -- Deep Learning -- A Divergent Index Advisor Using Deep Reinforcement Learning -- 1 Introduction -- 2 Related Work -- 3 DRL Divergent Index Selection Framework -- 3.1 Pre-processing Module -- 3.2 DRL Divergent Index Selection Module -- 3.3 The Cost Estimation Module -- 4 Experimental Results -- 4.1 Experimental Setup -- 5 Conclusion and Future Research -- References -- Deep Active Learning Framework for Crowdsourcing-Enhanced Image Classification and Segmentation -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Notation -- 3.2 Neural Networks for Image Tasks -- 3.3 Active Learning -- 4 Performance Evaluation -- 4.1 Crowdsourcing Image Classification via Active Learning -- 4.2 Crowdsourcing Image Segmentation via Active Learning -- 4.3 Analysis and Discussion -- 5 Conclusions and Perspectives -- References -- Sentiment and Knowledge Based Algorithmic Trading with Deep Reinforcement Learning -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 Reinforcement Learning -- 3.2 Sentiment Analysis -- 3.3 Knowledge Graphs -- 4 Empirical Evaluation -- 4.1 Data -- 4.2 MDP Formulation -- 5 Results and Analysis -- 5.1 Training Data Analysis -- 5.2 Test Data Analysis -- 5.3 Sharpe Ratio -- 6 Discussion and Conclusion -- References -- DeepCore: A Comprehensive Library for Coreset Selection in Deep Learning -- 1 Introduction -- 2 Review of Coreset Selection Methods -- 2.1 Problem Statement -- 2.2 Survey: Methodologies -- 2.3 Survey: Applications -- 3 DeepCore Library -- 4 Experiment Results -- 4.1 CIFAR10 Results -- 4.2 ImageNet Results -- 4.3 Cross-architecture Generalization -- 4.4 Sensitiveness to Pre-trained Models -- 5 Extended Related Work.
6 Conclusion -- References -- Context Iterative Learning for Aspect-Level Sentiment Classification -- 1 Introduction -- 2 Related Work -- 3 Context Attention Modules (CAM) -- 3.1 Intra-Multi-Headed Attention Mechanism (Intra-MHA) and Inter-Multi-Headed Attention Mechanism (Inter-MHA) -- 3.2 Context Features Dynamic Mask/Context Features Dynamic Weighted (CDM/CDW) -- 3.3 Position-Wise Feed-Forward Networks (PFFN) and Aspect-Context Representation Output -- 4 Context Iterative Learning Network (CILN) -- 4.1 Pooling Layer and Training -- 5 Experiment -- 5.1 Datasets and Experimental Settings -- 5.2 Baseline and Result -- 6 Conclusion -- References -- Smart Cities and Human Computing -- EcoLight: Eco-friendly Traffic Signal Control Driven by Urban Noise Prediction -- 1 Introduction -- 2 Related Work -- 2.1 Noise Prediction -- 2.2 Traffic Signal Control -- 3 Formalization of the Problem -- 4 EcoLight Approach -- 4.1 Traffic Noise Prediction -- 4.2 Traffic Signal Control -- 5 Experimental Evaluation -- 5.1 Dataset -- 5.2 Experimental Setups -- 5.3 Baseline Methods for Comparison -- 5.4 Evaluation -- 5.5 Results and Discussion -- 6 Conclusion -- References -- Mining Fluctuation Propagation Graph Among Time Series with Active Learning -- 1 Introduction -- 2 Related Work -- 3 Empirical Study of Mining Methods -- 3.1 Experimental Setup -- 3.2 Results -- 4 FPG-Miner: Mine with Active Learning -- 4.1 Recommendation Framework -- 4.2 Continuous Association Rule Classifier -- 5 Experiment -- 5.1 Experimental Setup -- 5.2 Results -- 5.3 Case Study: Root Cause Analysis -- 6 Conclusion -- References -- Towards Efficient Human Action Retrieval Based on Triplet-Loss Metric Learning -- 1 Introduction -- 2 Action Retrieval -- 2.1 Problem Definition -- 2.2 Retrieval Process -- 3 Learning Action Features -- 3.1 Triplet-Loss Learning -- 3.2 Triplet Generation Strategies.
4 Experimental Evaluation -- 4.1 Dataset -- 4.2 Methodology -- 4.3 Experimental Results -- 4.4 State-of-the-Art Comparison -- 5 Conclusions -- References -- KAPP: Knowledge-Aware Hierarchical Attention Network for Popularity Prediction -- 1 Introduction -- 2 Methodology -- 2.1 Knowledge-Aware User Embedding -- 2.2 Attention-Based Retweet Path Encoding -- 2.3 Prediction with Point Process -- 3 Experiments -- 3.1 Experiment Setup -- 3.2 Numerical Results -- 4 Conclusion -- References -- Advanced Machine Learning -- A Heterogeneous Network Representation Learning Approach for Academic Behavior Prediction -- 1 Introduction -- 2 Related Work -- 3 The Mechanism of HNEABP Approach -- 3.1 Balanced Walk Method Based on Edge Number -- 3.2 Balanced Walk Method Based on Edge Loss -- 3.3 Node Pair and Semantic Information Learning Based on KGE -- 3.4 Loss Function -- 3.5 HNEABP Algorithm -- 4 Verification Experiment on Node Representation Learning -- 4.1 Datasets and Baseline Methods -- 4.2 Experimental Setup and Evaluation Criteria -- 4.3 Analysis of Experimental Results -- 5 Conclusion -- References -- A Market Segmentation Aware Retail Itemset Placement Framework -- 1 Introduction -- 2 Related Work -- 3 Proposed Framework of Itemset Placement Problem -- 4 MATRIX and MIPS -- 5 Performance Evaluation -- 6 Conclusion -- References -- Label Selection Algorithm Based on Iteration Column Subset Selection for Multi-label Classification -- 1 Introduction -- 2 Multi-label Classification Using Iteration Column Subset Selection -- 2.1 Notation -- 2.2 Iteration Column Subset Selection -- 2.3 Building a Recovery Matrix -- 2.4 Learning the Model and Prediction -- 3 Experiments -- 3.1 Six Benchmark Data Sets and Two Evaluation Metrics -- 3.2 Experimental Settings -- 3.3 Results -- 4 Conclusions -- References.
Accurately Predicting User Registration in Highly Unbalanced Real-World Datasets from Online News Portals.
Record Nr. UNISA-996483156503316
Cham, Switzerland : , : Springer International Publishing, , [2022]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Database and expert systems applications . Part II : 33rd international conference, DEXA 2022, Vienna, Austria, August 22-24, 2022, proceedings / / Christine Strauss [and four others], editors
Database and expert systems applications . Part II : 33rd international conference, DEXA 2022, Vienna, Austria, August 22-24, 2022, proceedings / / Christine Strauss [and four others], editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer International Publishing, , [2022]
Descrizione fisica 1 online resource (333 pages)
Disciplina 005.7565
Collana Lecture Notes in Computer Science
Soggetto topico Database management
Expert systems (Computer science)
ISBN 3-031-12426-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Abstracts of Keynote Talks -- Responsible AI -- Following the Rules: From Policies to Norms -- Contents - Part II -- Contents - Part I -- Time Series, Streams and Event Data -- Clustering-Based Cross-Sectional Regime Identification for Financial Market Forecasting -- 1 Introduction -- 2 Related Work -- 3 The Proposed Model -- 3.1 Overview of the Proposed Model -- 3.2 Cluster-Based Regime Identification -- 3.3 Regime Modeling and Transition Probability Estimation -- 3.4 Financial Market Forecasting -- 4 Experiments -- 4.1 Dataset Description -- 4.2 Performance Metrics -- 4.3 Experimental Results and Discussion -- 5 Conclusion -- References -- Alps: An Adaptive Load Partitioning Scaling Solution for Stream Processing System on Skewed Stream*-6pt -- 1 Introduction -- 2 Related Work -- 3 Model and Algorithm Design -- 3.1 Algorithm Foundation -- 3.2 Operator Performance Model -- 3.3 Adaptive Partitioning Scaling -- 4 Evaluation -- 4.1 Setup -- 4.2 Adaptive Partitioning Scaling -- 4.3 Alps on Realistic Datasets -- 5 Conclusion -- References -- Latent Relational Point Process: Network Reconstruction from Discrete Event Data -- 1 Introduction -- 2 Related Work -- 3 Framework -- 3.1 General Framework -- 3.2 Evolutionary Framework -- 3.3 Estimation via Expectation Maximisation -- 3.4 Goodness-of-Fit Test -- 4 Empirical Evaluation -- 4.1 Simple Pair Model -- 4.2 Synthetic Data -- 4.3 Revisiting MIT Reality Mining -- 5 Conclusion -- A Appendix -- A.1 The Lower Bound of the Posterior -- A.2 The Surrogate is the Posterior Distribution -- A.3 Simple-Pair Model: Gilbert Graph -- References -- InTrans: Fast Incremental Transformer for Time Series Data Prediction -- 1 Introduction -- 2 Preliminaries -- 2.1 Time-Series Data -- 2.2 Informer -- 3 Incremental Transformer: InTrans -- 3.1 Motivation -- 3.2 Overview.
3.3 Incremental Positional Embedding -- 3.4 Incremental Temporal Embedding -- 3.5 Incremental Value Embedding -- 3.6 Incremental Self-Attention -- 3.7 Prediction Accuracy -- 3.8 Complexity Analysis -- 4 Experimental Evaluation -- 4.1 Dataset and Settings -- 4.2 Training and Testing Time Without GPU -- 4.3 Training and Testing Time Using a GPU -- 5 Related Works -- 6 Conclusion -- A Proof of Theorem 1 -- B Proof of Theorem 2 -- C Proof of Theorem 3 -- D Proof of Theorem 4 -- E Proof of Theorem 5 -- F Proof of Theorem 6 -- G Proof of Theorem 7 -- References -- A Knowledge-Driven Business Process Analysis Methodology -- 1 Introduction -- 2 Business Process Analysis Canvas -- 3 Applying the BPA Canvas: A Running Example -- 4 Building Class Diagrams and the BPA Ontology -- 5 Related Work and Conclusions -- References -- Sequences and Graphs -- Extending Authorization Capabilities of Object Relational/Graph Mappers by Request Manipulation -- 1 Introduction -- 2 Outline of the Problem -- 2.1 Stakeholder Goals -- 2.2 Problem Context -- 2.3 Artifact -- 3 Our Solution -- 3.1 Interception -- 3.2 Responsibility of the Wrapper -- 3.3 Encoding the Authorization Properties -- 3.4 Summary -- 4 Assessing the Prototype -- 4.1 Applicability of the Solution Concept -- 4.2 Performance -- 5 Related Work -- 5.1 Query Rewriting and Interception -- 5.2 Authorization in Databases -- 5.3 Common Access Control Approaches -- 6 Conclusion and Future Work -- References -- Sequence Recommendation Model with Double-Layer Attention Net -- 1 Introduction -- 2 Related Work -- 2.1 Traditional Sequential Recommendation Models -- 2.2 Deep Neural Network Models -- 2.3 Attention-Based Models -- 3 The Proposed Model: DAttRec -- 3.1 Symbolic Description -- 3.2 STAMP Model -- 3.3 DAttRec Model -- 4 Experiments -- 4.1 Datasets and Data Preparation -- 4.2 Evaluation Metrics.
4.3 Baselines -- 4.4 Parameters -- 4.5 Performance Comparison -- 4.6 Model Analysis and Discussion -- 5 Conclusion -- References -- Fault Detection in Seismic Data Using Graph Attention Network -- 1 Introduction -- 2 Description of Data -- 3 Extraction of Patches -- 4 Representation of Patches in the Graph Domain -- 5 Application of GAT -- 6 Experimental Results -- 7 Application on Field Seismic Data -- 8 Conclusion -- References -- Skeleton-Based Mutual Action Recognition Using Interactive Skeleton Graph and Joint Attention -- 1 Introduction -- 2 Our Model -- 2.1 GCN with Distance Grouping Strategy -- 2.2 Interactive Skeleton Graph -- 2.3 Joint Attention Module -- 3 Experimental Evaluation -- 3.1 Datasets -- 3.2 Results -- 4 Conclusion -- References -- Comparison of Sequence Variants and the Application in Electronic Medical Records -- 1 Introduction -- 2 Related Work -- 2.1 SPM -- 2.2 Analysis of Medical Data by SPM -- 2.3 Analysis of SVs -- 3 Proposed Methods -- 3.1 Sequence -- 3.2 SV -- 3.3 LCS -- 3.4 LCSV -- 3.5 MSV -- 4 Experiments -- 4.1 Experimental Method and Environment -- 4.2 Data Sets -- 4.3 Experimental Results -- 5 Conclusion and Future Work -- References -- Neural Networks -- Reconciliation of Mental Concepts with Graph Neural Networks -- 1 Introduction -- 2 Related Work -- 3 Asymmetric Bidirectional Residual GNN -- 4 Dataset -- 5 Experiments -- 5.1 Methodology -- 5.2 Predictive Performance -- 5.3 General Link Prediction on Citeseer -- 5.4 Ablation Studies -- 6 Conclusion -- References -- I-PNN: An Improved Probabilistic Neural Network for Binary Classification of Imbalanced Medical Data -- 1 Introduction -- 2 State-of-the-Arts -- 3 I-PNN: Improved PNN for Imbalanced Classification Tasks in Medicine -- 4 Modeling and Results -- 5 Comparison and Discusion -- 6 Conclusions and Future Work -- References.
PBRE: A Rule Extraction Method from Trained Neural Networks Designed for Smart Home Services -- 1 Introduction -- 2 Context and Related Work -- 3 The Proposed PBRE Method -- 3.1 Generate Instance Rules -- 3.2 Generalize Instance Rules -- 3.3 Combine Rules -- 3.4 Refine Rules -- 4 Evaluation and Comparison with Existing Work -- 4.1 Comparative Experiment -- 5 NRL and Rule Extraction Methods in the Smart Home -- 5.1 Smart Home System in Practice -- 5.2 Smart Home System in Simulation -- 6 Experiment in the Smart Home Context -- 6.1 Simulated Environment -- 6.2 Experiment Results -- 7 Conclusion -- Appendix 1 Datasets Descriptions -- Appendix 2 Metric Acquiring Procedure -- Appendix 3 Extracted Rules for Light Services -- References -- Effective and Robust Boundary-Based Outlier Detection Using Generative Adversarial Networks -- 1 Introduction -- 2 Related Work -- 3 Our Method -- 3.1 Initial Reference Boundary -- 3.2 Boundary-Based GAN -- 4 Experiments -- 4.1 Experiment Design -- 4.2 Experiment Results -- 5 Conclusion -- References -- Efficient Data Processing Techniques -- Accelerated Parallel Hybrid GPU/CPU Hash Table Queries with String Keys -- 1 Introduction -- 2 Related Work -- 3 Basics -- 3.1 Hash Tables -- 3.2 Hardware Acceleration -- 4 Parallel Hybrid GPU/CPU Hash Table for String Keys -- 4.1 Idea -- 4.2 Data Structure and Search -- 5 Evaluation -- 5.1 Benchmark Framework -- 5.2 Benchmark Environment -- 5.3 Benchmark Results -- 6 Summary and Conclusions -- References -- Towards Efficient Discovery of Periodic-Frequent Patterns in Dense Temporal Databases Using Complements -- 1 Introduction -- 2 Related Work -- 3 Periodic-Frequent Pattern Model -- 4 Proposed Algorithm -- 4.1 Basic Idea: Calculating the Periodicity of a Pattern Using Complements -- 4.2 PFPM-C -- 5 Experimental Results -- 5.1 Experimental Setup.
5.2 Generation of Periodic-Frequent Patterns -- 5.3 Runtime Evaluation of the Algorithms -- 5.4 Memory Evaluation of the Algorithms -- 6 Conclusions and Future Work -- References -- An Error-Bounded Space-Efficient Hybrid Learned Index with High Lookup Performance -- 1 Introduction -- 2 Related Work -- 3 Hybrid Learned Index -- 3.1 Overview -- 3.2 Leaf Nodes with Error Bound -- 3.3 Inner Nodes Without Error Bound -- 4 Performance Evaluation -- 4.1 Experimental Settings -- 4.2 Query Performance -- 4.3 Space Cost -- 4.4 Space-Time Trade-Off -- 5 Conclusions and Future Work -- References -- .26em plus .1em minus .1emContinuous Similarity Search for Text Sets -- 1 Introduction -- 2 Problem Statement -- 3 Our Algorithm for CTS -- 4 Usage of Inverted Indices -- 5 Experiments -- References -- Exploiting Embedded Synopsis for Exact and Approximate Query Processing -- 1 Introduction -- 2 Synopsis Embedment and Synopsis-Aware Search -- 3 Experiment -- 4 Related Work and Conclusion -- References -- Advanced Analytics Methodologies and Methods -- Diversity-Oriented Route Planning for Tourists -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Preliminary -- 3.2 Model -- 3.3 Real-Time Statistics of the External Environment -- 4 Experiment and Result -- 4.1 Experiment Setting -- 4.2 Evaluation Metrics -- 4.3 Experimental Result -- 5 Conclusion -- References -- Optimizing the Post-disaster Resource Allocation with Q-Learning: Demonstration of 2021 China Flood -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Model Architecture -- 3.2 Optimization Function -- 3.3 Reward Update (R) and State Update (S) -- 4 Experiment -- 4.1 Data Preparation -- 4.2 Numerical Experiment -- 4.3 Analysis of Results -- 5 Conclusion -- References -- ARDBS: Efficient Processing of Provenance Queries Over Annotated Relations -- 1 Introduction.
2 Semantic-Aware Query Processing.
Record Nr. UNINA-9910585783403321
Cham, Switzerland : , : Springer International Publishing, , [2022]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Database and expert systems applications . Part I : 33rd International Conference, DEXA 2022, Vienna, Austria, August 22-24, 2022, proceedings / / Christine Strauss [and four others], editors
Database and expert systems applications . Part I : 33rd International Conference, DEXA 2022, Vienna, Austria, August 22-24, 2022, proceedings / / Christine Strauss [and four others], editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer International Publishing, , [2022]
Descrizione fisica 1 online resource (469 pages)
Disciplina 005.7565
Collana Lecture Notes in Computer Science
Soggetto topico Database management
Expert systems (Computer science)
ISBN 3-031-12423-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Abstracts of Keynote Talks -- Responsible AI -- Following the Rules: From Policies to Norms -- Contents - Part I -- Contents - Part II -- Knowledge Graphs -- Jointly Learning Propagating Features on the Knowledge Graph for Movie Recommendation -- 1 Introduction -- 2 Methodology -- 2.1 Problem Formulation -- 2.2 Heterogeneous Graph Construction -- 2.3 The Proposed Framework -- 3 Experiments -- 3.1 Datasets -- 3.2 Experimental Settings -- 3.3 Experimental Results -- 3.4 Ablation Study -- 4 Conclusion -- References -- Syntax-Informed Question Answering with Heterogeneous Graph Transformer -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Graph Creation Module -- 3.2 Graph Processing and Answer Prediction -- 4 Experiments and Discussions -- 4.1 Setup -- 4.2 Evaluation -- 4.3 LingHGT, SemHGT, PragHGT: Towards Linguistics-Informed Language Models -- 5 Conclusion -- References -- Automated Process Knowledge Graph Construction from BPMN Models -- 1 Introduction -- 2 Background -- 3 Industrial Use Case -- 4 BPMN2KG Tool -- 4.1 Requirements -- 4.2 Process Knowledge Graph Construction -- 4.3 Implementation -- 5 Application Scenarios -- 6 Related Work -- 7 Conclusions -- A SPARQL Queries and Results -- References -- CAKE: A Context-Aware Knowledge Embedding Model of Knowledge Graph -- 1 Introduction -- 2 Related Work -- 3 Context-Aware Knowledge Embedding (CAKE) -- 3.1 LDA-Based Context Learning -- 3.2 HDP-Based Context Learning -- 3.3 Context-Aware Knowledge Embedding -- 4 Experimental Evaluation -- 4.1 Experiment Protocol -- 4.2 Experiment Settings -- 4.3 Experimental Results -- 5 Conclusion -- A Appendix: Optimization of CAKE -- References -- The Digitalization of Bioassays in the Open Research Knowledge Graph -- 1 Introduction -- 2 Bioassay Digitalization in the ORKG -- 3 Conclusion -- References.
Privacy-Preservation Approaches -- Privacy Issues in Smart Grid Data: From Energy Disaggregation to Disclosure Risk -- 1 Introduction -- 2 Related Work -- 2.1 Non-intrusive Load Monitoring -- 2.2 Privacy Preserving Data Publishing in Smart Grid -- 3 Proposed Method for Disclosure Risk Assessment -- 3.1 Appliance Selection -- 3.2 Seq2Seq Disaggregation Algorithm -- 3.3 Event Detection -- 3.4 Middle-Point Thresholding -- 3.5 Variance-Sensitive Thresholding -- 3.6 Activation Time Extraction -- 3.7 Disaggregation Risk -- 4 Experimental Setup -- 4.1 Datasets -- 4.2 Training and Testing Period -- 4.3 Threshold Computation -- 5 Results and Discussion -- 5.1 Inference Attack on the Same Building -- 5.2 Inference Attack on Different Buildings in the Same Dataset -- 5.3 Inference Attack on Different Buildings from Different Datasets -- 6 Conclusion -- References -- CoK: A Survey of Privacy Challenges in Relation to Data Meshes -- 1 Introduction -- 2 State-of-the-Art -- 2.1 Data Mesh Databases -- 2.2 Privacy in Mesh Networking -- 2.3 Syntactic Data Anonymisation -- 2.4 Semantic Data Anonymisation and Differential Privacy -- 2.5 Unique Column Combinations -- 2.6 High-Dimensional Data -- 2.7 Quasi-Identifier Discovery -- 3 Data Meshes -- 4 Experiments -- 5 Conclusion and Future Directions -- References -- Why- and How-Provenance in Distributed Environments -- 1 Introduction -- 2 Background and Related Work -- 2.1 Data Provenance -- 2.2 Distributed Databases -- 2.3 Related Work -- 3 Provenance in Distributed Databases -- 3.1 Architecture -- 3.2 Annotations -- 3.3 Build Provenance Information -- 4 Experimental Evaluation -- 5 Conclusions and Future Work -- References -- Provenance-Based SPARQL Query Formulation -- 1 Introduction -- 2 Model -- 3 Structural Edits -- 4 Grounding Generator -- 5 Procuring Feedback -- 6 Experiments -- 7 Related Work -- 8 Conclusion.
References -- Anonymisation of Heterogeneous Graphs with Multiple Edge Types -- 1 Introduction -- 2 K-RDF-Neighbourhood Anonymisation with Multiple Edge Types -- 3 Conclusions -- References -- Deep Learning -- A Divergent Index Advisor Using Deep Reinforcement Learning -- 1 Introduction -- 2 Related Work -- 3 DRL Divergent Index Selection Framework -- 3.1 Pre-processing Module -- 3.2 DRL Divergent Index Selection Module -- 3.3 The Cost Estimation Module -- 4 Experimental Results -- 4.1 Experimental Setup -- 5 Conclusion and Future Research -- References -- Deep Active Learning Framework for Crowdsourcing-Enhanced Image Classification and Segmentation -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Notation -- 3.2 Neural Networks for Image Tasks -- 3.3 Active Learning -- 4 Performance Evaluation -- 4.1 Crowdsourcing Image Classification via Active Learning -- 4.2 Crowdsourcing Image Segmentation via Active Learning -- 4.3 Analysis and Discussion -- 5 Conclusions and Perspectives -- References -- Sentiment and Knowledge Based Algorithmic Trading with Deep Reinforcement Learning -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 Reinforcement Learning -- 3.2 Sentiment Analysis -- 3.3 Knowledge Graphs -- 4 Empirical Evaluation -- 4.1 Data -- 4.2 MDP Formulation -- 5 Results and Analysis -- 5.1 Training Data Analysis -- 5.2 Test Data Analysis -- 5.3 Sharpe Ratio -- 6 Discussion and Conclusion -- References -- DeepCore: A Comprehensive Library for Coreset Selection in Deep Learning -- 1 Introduction -- 2 Review of Coreset Selection Methods -- 2.1 Problem Statement -- 2.2 Survey: Methodologies -- 2.3 Survey: Applications -- 3 DeepCore Library -- 4 Experiment Results -- 4.1 CIFAR10 Results -- 4.2 ImageNet Results -- 4.3 Cross-architecture Generalization -- 4.4 Sensitiveness to Pre-trained Models -- 5 Extended Related Work.
6 Conclusion -- References -- Context Iterative Learning for Aspect-Level Sentiment Classification -- 1 Introduction -- 2 Related Work -- 3 Context Attention Modules (CAM) -- 3.1 Intra-Multi-Headed Attention Mechanism (Intra-MHA) and Inter-Multi-Headed Attention Mechanism (Inter-MHA) -- 3.2 Context Features Dynamic Mask/Context Features Dynamic Weighted (CDM/CDW) -- 3.3 Position-Wise Feed-Forward Networks (PFFN) and Aspect-Context Representation Output -- 4 Context Iterative Learning Network (CILN) -- 4.1 Pooling Layer and Training -- 5 Experiment -- 5.1 Datasets and Experimental Settings -- 5.2 Baseline and Result -- 6 Conclusion -- References -- Smart Cities and Human Computing -- EcoLight: Eco-friendly Traffic Signal Control Driven by Urban Noise Prediction -- 1 Introduction -- 2 Related Work -- 2.1 Noise Prediction -- 2.2 Traffic Signal Control -- 3 Formalization of the Problem -- 4 EcoLight Approach -- 4.1 Traffic Noise Prediction -- 4.2 Traffic Signal Control -- 5 Experimental Evaluation -- 5.1 Dataset -- 5.2 Experimental Setups -- 5.3 Baseline Methods for Comparison -- 5.4 Evaluation -- 5.5 Results and Discussion -- 6 Conclusion -- References -- Mining Fluctuation Propagation Graph Among Time Series with Active Learning -- 1 Introduction -- 2 Related Work -- 3 Empirical Study of Mining Methods -- 3.1 Experimental Setup -- 3.2 Results -- 4 FPG-Miner: Mine with Active Learning -- 4.1 Recommendation Framework -- 4.2 Continuous Association Rule Classifier -- 5 Experiment -- 5.1 Experimental Setup -- 5.2 Results -- 5.3 Case Study: Root Cause Analysis -- 6 Conclusion -- References -- Towards Efficient Human Action Retrieval Based on Triplet-Loss Metric Learning -- 1 Introduction -- 2 Action Retrieval -- 2.1 Problem Definition -- 2.2 Retrieval Process -- 3 Learning Action Features -- 3.1 Triplet-Loss Learning -- 3.2 Triplet Generation Strategies.
4 Experimental Evaluation -- 4.1 Dataset -- 4.2 Methodology -- 4.3 Experimental Results -- 4.4 State-of-the-Art Comparison -- 5 Conclusions -- References -- KAPP: Knowledge-Aware Hierarchical Attention Network for Popularity Prediction -- 1 Introduction -- 2 Methodology -- 2.1 Knowledge-Aware User Embedding -- 2.2 Attention-Based Retweet Path Encoding -- 2.3 Prediction with Point Process -- 3 Experiments -- 3.1 Experiment Setup -- 3.2 Numerical Results -- 4 Conclusion -- References -- Advanced Machine Learning -- A Heterogeneous Network Representation Learning Approach for Academic Behavior Prediction -- 1 Introduction -- 2 Related Work -- 3 The Mechanism of HNEABP Approach -- 3.1 Balanced Walk Method Based on Edge Number -- 3.2 Balanced Walk Method Based on Edge Loss -- 3.3 Node Pair and Semantic Information Learning Based on KGE -- 3.4 Loss Function -- 3.5 HNEABP Algorithm -- 4 Verification Experiment on Node Representation Learning -- 4.1 Datasets and Baseline Methods -- 4.2 Experimental Setup and Evaluation Criteria -- 4.3 Analysis of Experimental Results -- 5 Conclusion -- References -- A Market Segmentation Aware Retail Itemset Placement Framework -- 1 Introduction -- 2 Related Work -- 3 Proposed Framework of Itemset Placement Problem -- 4 MATRIX and MIPS -- 5 Performance Evaluation -- 6 Conclusion -- References -- Label Selection Algorithm Based on Iteration Column Subset Selection for Multi-label Classification -- 1 Introduction -- 2 Multi-label Classification Using Iteration Column Subset Selection -- 2.1 Notation -- 2.2 Iteration Column Subset Selection -- 2.3 Building a Recovery Matrix -- 2.4 Learning the Model and Prediction -- 3 Experiments -- 3.1 Six Benchmark Data Sets and Two Evaluation Metrics -- 3.2 Experimental Settings -- 3.3 Results -- 4 Conclusions -- References.
Accurately Predicting User Registration in Highly Unbalanced Real-World Datasets from Online News Portals.
Record Nr. UNINA-9910585783003321
Cham, Switzerland : , : Springer International Publishing, , [2022]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Database and expert systems applications . Part II : 33rd international conference, DEXA 2022, Vienna, Austria, August 22-24, 2022, proceedings / / Christine Strauss [and four others], editors
Database and expert systems applications . Part II : 33rd international conference, DEXA 2022, Vienna, Austria, August 22-24, 2022, proceedings / / Christine Strauss [and four others], editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer International Publishing, , [2022]
Descrizione fisica 1 online resource (333 pages)
Disciplina 005.7565
Collana Lecture Notes in Computer Science
Soggetto topico Database management
Expert systems (Computer science)
ISBN 3-031-12426-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Abstracts of Keynote Talks -- Responsible AI -- Following the Rules: From Policies to Norms -- Contents - Part II -- Contents - Part I -- Time Series, Streams and Event Data -- Clustering-Based Cross-Sectional Regime Identification for Financial Market Forecasting -- 1 Introduction -- 2 Related Work -- 3 The Proposed Model -- 3.1 Overview of the Proposed Model -- 3.2 Cluster-Based Regime Identification -- 3.3 Regime Modeling and Transition Probability Estimation -- 3.4 Financial Market Forecasting -- 4 Experiments -- 4.1 Dataset Description -- 4.2 Performance Metrics -- 4.3 Experimental Results and Discussion -- 5 Conclusion -- References -- Alps: An Adaptive Load Partitioning Scaling Solution for Stream Processing System on Skewed Stream*-6pt -- 1 Introduction -- 2 Related Work -- 3 Model and Algorithm Design -- 3.1 Algorithm Foundation -- 3.2 Operator Performance Model -- 3.3 Adaptive Partitioning Scaling -- 4 Evaluation -- 4.1 Setup -- 4.2 Adaptive Partitioning Scaling -- 4.3 Alps on Realistic Datasets -- 5 Conclusion -- References -- Latent Relational Point Process: Network Reconstruction from Discrete Event Data -- 1 Introduction -- 2 Related Work -- 3 Framework -- 3.1 General Framework -- 3.2 Evolutionary Framework -- 3.3 Estimation via Expectation Maximisation -- 3.4 Goodness-of-Fit Test -- 4 Empirical Evaluation -- 4.1 Simple Pair Model -- 4.2 Synthetic Data -- 4.3 Revisiting MIT Reality Mining -- 5 Conclusion -- A Appendix -- A.1 The Lower Bound of the Posterior -- A.2 The Surrogate is the Posterior Distribution -- A.3 Simple-Pair Model: Gilbert Graph -- References -- InTrans: Fast Incremental Transformer for Time Series Data Prediction -- 1 Introduction -- 2 Preliminaries -- 2.1 Time-Series Data -- 2.2 Informer -- 3 Incremental Transformer: InTrans -- 3.1 Motivation -- 3.2 Overview.
3.3 Incremental Positional Embedding -- 3.4 Incremental Temporal Embedding -- 3.5 Incremental Value Embedding -- 3.6 Incremental Self-Attention -- 3.7 Prediction Accuracy -- 3.8 Complexity Analysis -- 4 Experimental Evaluation -- 4.1 Dataset and Settings -- 4.2 Training and Testing Time Without GPU -- 4.3 Training and Testing Time Using a GPU -- 5 Related Works -- 6 Conclusion -- A Proof of Theorem 1 -- B Proof of Theorem 2 -- C Proof of Theorem 3 -- D Proof of Theorem 4 -- E Proof of Theorem 5 -- F Proof of Theorem 6 -- G Proof of Theorem 7 -- References -- A Knowledge-Driven Business Process Analysis Methodology -- 1 Introduction -- 2 Business Process Analysis Canvas -- 3 Applying the BPA Canvas: A Running Example -- 4 Building Class Diagrams and the BPA Ontology -- 5 Related Work and Conclusions -- References -- Sequences and Graphs -- Extending Authorization Capabilities of Object Relational/Graph Mappers by Request Manipulation -- 1 Introduction -- 2 Outline of the Problem -- 2.1 Stakeholder Goals -- 2.2 Problem Context -- 2.3 Artifact -- 3 Our Solution -- 3.1 Interception -- 3.2 Responsibility of the Wrapper -- 3.3 Encoding the Authorization Properties -- 3.4 Summary -- 4 Assessing the Prototype -- 4.1 Applicability of the Solution Concept -- 4.2 Performance -- 5 Related Work -- 5.1 Query Rewriting and Interception -- 5.2 Authorization in Databases -- 5.3 Common Access Control Approaches -- 6 Conclusion and Future Work -- References -- Sequence Recommendation Model with Double-Layer Attention Net -- 1 Introduction -- 2 Related Work -- 2.1 Traditional Sequential Recommendation Models -- 2.2 Deep Neural Network Models -- 2.3 Attention-Based Models -- 3 The Proposed Model: DAttRec -- 3.1 Symbolic Description -- 3.2 STAMP Model -- 3.3 DAttRec Model -- 4 Experiments -- 4.1 Datasets and Data Preparation -- 4.2 Evaluation Metrics.
4.3 Baselines -- 4.4 Parameters -- 4.5 Performance Comparison -- 4.6 Model Analysis and Discussion -- 5 Conclusion -- References -- Fault Detection in Seismic Data Using Graph Attention Network -- 1 Introduction -- 2 Description of Data -- 3 Extraction of Patches -- 4 Representation of Patches in the Graph Domain -- 5 Application of GAT -- 6 Experimental Results -- 7 Application on Field Seismic Data -- 8 Conclusion -- References -- Skeleton-Based Mutual Action Recognition Using Interactive Skeleton Graph and Joint Attention -- 1 Introduction -- 2 Our Model -- 2.1 GCN with Distance Grouping Strategy -- 2.2 Interactive Skeleton Graph -- 2.3 Joint Attention Module -- 3 Experimental Evaluation -- 3.1 Datasets -- 3.2 Results -- 4 Conclusion -- References -- Comparison of Sequence Variants and the Application in Electronic Medical Records -- 1 Introduction -- 2 Related Work -- 2.1 SPM -- 2.2 Analysis of Medical Data by SPM -- 2.3 Analysis of SVs -- 3 Proposed Methods -- 3.1 Sequence -- 3.2 SV -- 3.3 LCS -- 3.4 LCSV -- 3.5 MSV -- 4 Experiments -- 4.1 Experimental Method and Environment -- 4.2 Data Sets -- 4.3 Experimental Results -- 5 Conclusion and Future Work -- References -- Neural Networks -- Reconciliation of Mental Concepts with Graph Neural Networks -- 1 Introduction -- 2 Related Work -- 3 Asymmetric Bidirectional Residual GNN -- 4 Dataset -- 5 Experiments -- 5.1 Methodology -- 5.2 Predictive Performance -- 5.3 General Link Prediction on Citeseer -- 5.4 Ablation Studies -- 6 Conclusion -- References -- I-PNN: An Improved Probabilistic Neural Network for Binary Classification of Imbalanced Medical Data -- 1 Introduction -- 2 State-of-the-Arts -- 3 I-PNN: Improved PNN for Imbalanced Classification Tasks in Medicine -- 4 Modeling and Results -- 5 Comparison and Discusion -- 6 Conclusions and Future Work -- References.
PBRE: A Rule Extraction Method from Trained Neural Networks Designed for Smart Home Services -- 1 Introduction -- 2 Context and Related Work -- 3 The Proposed PBRE Method -- 3.1 Generate Instance Rules -- 3.2 Generalize Instance Rules -- 3.3 Combine Rules -- 3.4 Refine Rules -- 4 Evaluation and Comparison with Existing Work -- 4.1 Comparative Experiment -- 5 NRL and Rule Extraction Methods in the Smart Home -- 5.1 Smart Home System in Practice -- 5.2 Smart Home System in Simulation -- 6 Experiment in the Smart Home Context -- 6.1 Simulated Environment -- 6.2 Experiment Results -- 7 Conclusion -- Appendix 1 Datasets Descriptions -- Appendix 2 Metric Acquiring Procedure -- Appendix 3 Extracted Rules for Light Services -- References -- Effective and Robust Boundary-Based Outlier Detection Using Generative Adversarial Networks -- 1 Introduction -- 2 Related Work -- 3 Our Method -- 3.1 Initial Reference Boundary -- 3.2 Boundary-Based GAN -- 4 Experiments -- 4.1 Experiment Design -- 4.2 Experiment Results -- 5 Conclusion -- References -- Efficient Data Processing Techniques -- Accelerated Parallel Hybrid GPU/CPU Hash Table Queries with String Keys -- 1 Introduction -- 2 Related Work -- 3 Basics -- 3.1 Hash Tables -- 3.2 Hardware Acceleration -- 4 Parallel Hybrid GPU/CPU Hash Table for String Keys -- 4.1 Idea -- 4.2 Data Structure and Search -- 5 Evaluation -- 5.1 Benchmark Framework -- 5.2 Benchmark Environment -- 5.3 Benchmark Results -- 6 Summary and Conclusions -- References -- Towards Efficient Discovery of Periodic-Frequent Patterns in Dense Temporal Databases Using Complements -- 1 Introduction -- 2 Related Work -- 3 Periodic-Frequent Pattern Model -- 4 Proposed Algorithm -- 4.1 Basic Idea: Calculating the Periodicity of a Pattern Using Complements -- 4.2 PFPM-C -- 5 Experimental Results -- 5.1 Experimental Setup.
5.2 Generation of Periodic-Frequent Patterns -- 5.3 Runtime Evaluation of the Algorithms -- 5.4 Memory Evaluation of the Algorithms -- 6 Conclusions and Future Work -- References -- An Error-Bounded Space-Efficient Hybrid Learned Index with High Lookup Performance -- 1 Introduction -- 2 Related Work -- 3 Hybrid Learned Index -- 3.1 Overview -- 3.2 Leaf Nodes with Error Bound -- 3.3 Inner Nodes Without Error Bound -- 4 Performance Evaluation -- 4.1 Experimental Settings -- 4.2 Query Performance -- 4.3 Space Cost -- 4.4 Space-Time Trade-Off -- 5 Conclusions and Future Work -- References -- .26em plus .1em minus .1emContinuous Similarity Search for Text Sets -- 1 Introduction -- 2 Problem Statement -- 3 Our Algorithm for CTS -- 4 Usage of Inverted Indices -- 5 Experiments -- References -- Exploiting Embedded Synopsis for Exact and Approximate Query Processing -- 1 Introduction -- 2 Synopsis Embedment and Synopsis-Aware Search -- 3 Experiment -- 4 Related Work and Conclusion -- References -- Advanced Analytics Methodologies and Methods -- Diversity-Oriented Route Planning for Tourists -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Preliminary -- 3.2 Model -- 3.3 Real-Time Statistics of the External Environment -- 4 Experiment and Result -- 4.1 Experiment Setting -- 4.2 Evaluation Metrics -- 4.3 Experimental Result -- 5 Conclusion -- References -- Optimizing the Post-disaster Resource Allocation with Q-Learning: Demonstration of 2021 China Flood -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Model Architecture -- 3.2 Optimization Function -- 3.3 Reward Update (R) and State Update (S) -- 4 Experiment -- 4.1 Data Preparation -- 4.2 Numerical Experiment -- 4.3 Analysis of Results -- 5 Conclusion -- References -- ARDBS: Efficient Processing of Provenance Queries Over Annotated Relations -- 1 Introduction.
2 Semantic-Aware Query Processing.
Record Nr. UNISA-996483156403316
Cham, Switzerland : , : Springer International Publishing, , [2022]
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Lo trovi qui: Univ. di Salerno
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Database and expert systems applications : 32nd international conference, DEXA 2021, virtual event, September 27-30, 2021, proceedings, part I / / Christine Strauss [and three others], editors
Database and expert systems applications : 32nd international conference, DEXA 2021, virtual event, September 27-30, 2021, proceedings, part I / / Christine Strauss [and three others], editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (412 pages)
Disciplina 005.74
Collana Lecture Notes in Computer Science
Soggetto topico Database management
Expert systems (Computer science)
ISBN 3-030-86472-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910495164903321
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Database and expert systems applications . Part II : 32nd international conference, DEXA 2021, virtual event, September 27-30, 2021 : proceedings / / Christine Strauss [and three others], (editors)
Database and expert systems applications . Part II : 32nd international conference, DEXA 2021, virtual event, September 27-30, 2021 : proceedings / / Christine Strauss [and three others], (editors)
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (377 pages)
Disciplina 005.74
Collana Lecture notes in computer science
Soggetto topico Database management
ISBN 3-030-86475-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Abstracts of Keynote Talks -- Privacy in the Era of Big Data, Machine Learning, IoT, and 5G -- Don't Handicap AI without Explicit Knowledge -- Extreme-Scale Model-Based Time Series Management with ModelarDB -- Big Minds Sharing their Vision on the Future of AI (Panel) -- Contents - Part II -- Contents - Part I -- Authenticity, Privacy, Security and Trust -- Less is More: Feature Choosing under Privacy-Preservation for Efficient Web Spam Detection -- 1 Introduction -- 2 The PPGAFS Approach -- 2.1 Preselecting Privacy-Preserving Features -- 2.2 Generating Minimum Feature Subset Based on the Improved GA -- 3 Spam Detection and Verification Experiment Analysis -- 3.1 Web Spam Detection Procedure -- 3.2 Dataset and Evaluation Measures -- 3.3 Experiment Design and Result Analysis -- 4 Conclusion -- References -- Construction of Differentially Private Summaries Over Fully Homomorphic Encryption -- 1 Introduction -- 2 Preliminaries -- 2.1 Homomorphic Encryption -- 2.2 Differential Privacy -- 3 Related Work -- 3.1 Combination of Homomorphic Encryption and Differential Privacy -- 3.2 Range Queries Under Differential Privacy -- 4 Proposed Method -- 4.1 Overview -- 4.2 Adoption of Differential Privacy over Fully Homomorphic Encryption -- 4.3 Security Analysis -- 5 Experimental Evaluation -- 5.1 Experimental Setup -- 5.2 DP-Summary Construction Time -- 5.3 Accuracy of DP-Summary -- 6 Conclusion -- References -- SafecareOnto: A Cyber-Physical Security Ontology for Healthcare Systems -- 1 Introduction -- 2 Safecare Ontology -- 3 Knowledge Acquisition -- 4 Formalization and Implementation -- 4.1 Concepts Identification -- 4.2 Relationships Identification -- 4.3 Axioms Definition -- 4.4 Implementation -- 5 Safecare Use Cases -- 6 Related Work -- 7 Conclusion -- References.
Repurpose Image Identification for Fake News Detection -- 1 Introduction -- 2 Related Work -- 3 Proposed Framework -- 3.1 Event Type Classifier -- 3.2 Image Repurpose Detector -- 4 Experimental Evaluation -- 4.1 Experimental Datasets -- 4.2 Experiments on Event Type Classification -- 4.3 Comparative Study -- 4.4 Variants of RECAST -- 4.5 Case Study -- 5 Conclusion -- References -- Data and Information Processing -- An Urgency-Aware and Revenue-Based Itemset Placement Framework for Retail Stores -- 1 Introduction -- 2 Proposed Framework of the Problem -- 3 URIP: Urgency-Aware Itemset Placement Scheme -- 4 Performance Evaluation -- 5 Conclusion -- References -- NV-QALSH: An NVM-Optimized Implementation of Query-Aware Locality-Sensitive Hashing -- 1 Introduction -- 2 Preliminaries -- 2.1 The c-ANN Search Problem -- 2.2 The QALSH Method -- 2.3 Non-Volatile Memory -- 2.4 LB-Tree and LB-QALSH -- 3 Optimization Designs -- 3.1 Three-Level Storage Architecture -- 3.2 Leaf Node Optimization -- 3.3 Collision Counting Granularity Optimization -- 4 Experiments -- 4.1 Experiment Setup -- 4.2 Datasets and Queries -- 4.3 Evaluation Metrics -- 4.4 Benchmark Methods -- 4.5 Results and Analysis -- 5 Conclusion -- References -- NCRedis: An NVM-Optimized Redis with Memory Caching -- 1 Introduction -- 2 Implementation of NCRedis -- 2.1 Architecture of NCRedis -- 2.2 Log-Free Designs of LFSlab -- 2.3 Handling Persistent Memory Leak by LFSlab -- 2.4 Log-Free Designs of NCRedis -- 3 Evaluation -- 3.1 Experimental Setup -- 3.2 Memtier Benchmark Test -- 4 Conclusions -- References -- A Highly Modular Architecture for Canned Pattern Selection Problem -- 1 Introduction -- 2 System Architecture -- 2.1 Graph Similarity Module -- 2.2 Graph Clustering Module -- 2.3 Graph Connection Module -- 2.4 Pattern Mining Module -- 3 Conclusions -- References -- AutoEncoder for Neuroimage.
1 Introduction -- 2 The Proposed Approach -- 2.1 Variational AutoEncoder Based Regression -- 2.2 Supervised Linear Autoencoder -- 2.3 Implementation Details -- 3 Experiments -- 4 Conclusion -- References -- Knowledge Discovery -- Towards New Model for Handling Inconsistency Issues in DL-Lite Knowledge Bases -- 1 Introduction -- 2 Related Works -- 3 DL-Lite Ontology and Management of Inconsistencies: An Overview -- 4 Most-Possible Repair Proposed Approach -- 4.1 Most-Possible Repair Algorithm -- 4.2 Experimental Study and Results Analysis -- 5 Conclusion and Prospects -- References -- ContextWalk: Embedding Networks with Context Information Extracted from News Articles -- 1 Introduction -- 2 Related Work -- 3 Dataset -- 3.1 Challenges -- 4 Algorithm -- 4.1 Context Embedding -- 4.2 ContextWalk -- 4.3 Complexity -- 5 Experiments -- 5.1 Compare Clusterings -- 5.2 Network and Embedding Distances -- 6 Discussion -- References -- FIP-SHA - Finding Individual Profiles Through SHared Accounts -- 1 Introduction -- 2 Background -- 3 Related Work -- 4 FIP-SHA -- 4.1 Session Representation -- 5 Experimental Evaluation Setup and Metrics -- 6 Results -- 6.1 Cut Off Sessions -- 6.2 Clustering -- 6.3 Analysis of (Weighted) User Separation -- 6.4 Discussion -- 7 Final Considerations -- References -- A Tag-Based Transformer Community Question Answering Learning-to-Rank Model in the Home Improvement Domain -- 1 Introduction -- 2 Related Work -- 3 Task Definition -- 4 Our Approach -- 4.1 Transformer Models -- 4.2 Input and Tag Representation -- 4.3 CQA Pair Matching Model -- 4.4 Model Optimisation -- 4.5 Candidate Answers Ranking -- 5 Dataset Building and Validation -- 5.1 Subjective CQA -- 5.2 Gold Standard Definition -- 6 Evaluation -- 6.1 Experiment Setup -- 6.2 Rank-Aware Evaluation Metrics -- 6.3 Results -- 7 Conclusion -- References.
An Autonomous Crowdsourcing System -- 1 Introduction -- 2 Related Work -- 3 Crowdsourcing Task -- 3.1 Workflow -- 4 Experimental Evaluation -- 4.1 Experimental Setup -- 4.2 Results -- 5 Conclusion -- References -- Machine Learning -- The Effect of IoT Data Completeness and Correctness on Explainable Machine Learning Models -- 1 Introduction -- 2 Related Work -- 3 Method -- 4 Observation, Analysis and Validation -- 5 Conclusion -- References -- Analysis of Behavioral Facilitation Tweets for Large-Scale Natural Disasters Dataset Using Machine Learning -- 1 Introduction -- 2 Related Work -- 3 Extraction of Behavioral Facilitation Tweets -- 3.1 A Classifier Based on LSTM -- 3.2 A Classifier Based on BiLSTM -- 3.3 A Classifier Based on BERT -- 4 Experiment 1: Comparison of Models for Classification Accuracy -- 4.1 Data -- 4.2 Method -- 4.3 Result -- 5 Experiment 2: Analysis Characteristics of BF-Tweets in a Large-Scale Disaster Situation -- 5.1 Experimental Conditions -- 5.2 Results -- 5.3 Discussion -- 6 Conclusion -- References -- Using Cross Lingual Learning for Detecting Hate Speech in Portuguese -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Evaluation and Results -- 5 Final Remarks -- References -- MMEnsemble: Imbalanced Classification Framework Using Metric Learning and Multi-sampling Ratio Ensemble -- 1 Introduction -- 2 Related Work: Resampling Approaches -- 2.1 Oversampling -- 2.2 Undersampling -- 3 MMEnsemble -- 3.1 Base Ensemble Classifier - MLEnsemble -- 3.2 Ensemble Using Asset-Based Weighting -- 4 Experimental Evaluation -- 4.1 Settings -- 4.2 Results -- 4.3 Lessons Learned -- 5 Conclusion -- References -- Evaluate the Contribution of Multiple Participants in Federated Learning -- 1 Introduction -- 2 Method -- 2.1 Shapley Value for Models -- 2.2 Invalid Shapley Value -- 2.3 Method -- 2.4 Properties -- 3 Experiment.
3.1 Utility Function -- 3.2 Noisy Labels -- 4 Conclusion -- References -- DFL-Net: Effective Object Detection via Distinguishable Feature Learning -- 1 Introduction -- 2 Related Work -- 3 Design of DFL-Net -- 3.1 High-Level Idea of DFL-Net -- 3.2 Full-Scale Fusion -- 3.3 Attention Guided Feature Refinement -- 4 Performance Evaluation -- 4.1 Settings -- 4.2 Results -- 4.3 Ablation Study -- 5 Conclusion and Future Work -- References -- Transfer Learning for Larger, Broader, and Deeper Neural-Network Quantum States -- 1 Introduction -- 2 Related Work -- 3 Background -- 3.1 Quantum Many-Body Systems -- 3.2 Deep Neural-Network Quantum States -- 4 Methodology -- 5 Performance Evaluation -- 5.1 Broader Networks -- 5.2 Deeper Networks -- 6 Conclusion -- References -- LGTM: A Fast and Accurate kNN Search Algorithm in High-Dimensional Spaces -- 1 Introduction -- 2 Theoretical Motivation -- 2.1 Preliminary -- 2.2 Theoretical Foundation -- 3 LGTM: From Theory to Practice -- 3.1 Pre-processing -- 3.2 Online (Query) Processing -- 4 Experiment -- 4.1 Comparison with AKNNG -- 4.2 Comparison with State-of-the-art Algorithms -- 5 Conclusion -- References -- TSX-Means: An Optimal K Search Approach for Time Series Clustering -- 1 Introduction -- 2 Notations and Definitions -- 3 TSX-Means: A New Method for Time Series Clustering -- 3.1 Principle of the Method -- 3.2 TSX-Means Algorithm -- 4 Experimental Results -- 5 Conclusion and Perspectives -- References -- A Globally Optimal Label Selection Method via Genetic Algorithm for Multi-label Classification -- 1 Introduction -- 2 Preliminaries -- 3 The Proposed Method -- 3.1 Uninformative Label Reduction via EBMD -- 3.2 Most Informative Label Selection via GA -- 3.3 Label Selection Algorithm Combining EBMD and GA -- 4 Experiments -- 4.1 Basic Experimental Settings -- 4.2 Experimental Results and Analysis -- 5 Conclusions.
References.
Record Nr. UNINA-9910495195003321
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Database and expert systems applications : 32nd international conference, DEXA 2021, virtual event, September 27-30, 2021, proceedings, part I / / Christine Strauss [and three others], editors
Database and expert systems applications : 32nd international conference, DEXA 2021, virtual event, September 27-30, 2021, proceedings, part I / / Christine Strauss [and three others], editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (412 pages)
Disciplina 005.74
Collana Lecture Notes in Computer Science
Soggetto topico Database management
Expert systems (Computer science)
ISBN 3-030-86472-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISA-996464488603316
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Database and expert systems applications . Part II : 32nd international conference, DEXA 2021, virtual event, September 27-30, 2021 : proceedings / / Christine Strauss [and three others], (editors)
Database and expert systems applications . Part II : 32nd international conference, DEXA 2021, virtual event, September 27-30, 2021 : proceedings / / Christine Strauss [and three others], (editors)
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (377 pages)
Disciplina 005.74
Collana Lecture notes in computer science
Soggetto topico Database management
ISBN 3-030-86475-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Abstracts of Keynote Talks -- Privacy in the Era of Big Data, Machine Learning, IoT, and 5G -- Don't Handicap AI without Explicit Knowledge -- Extreme-Scale Model-Based Time Series Management with ModelarDB -- Big Minds Sharing their Vision on the Future of AI (Panel) -- Contents - Part II -- Contents - Part I -- Authenticity, Privacy, Security and Trust -- Less is More: Feature Choosing under Privacy-Preservation for Efficient Web Spam Detection -- 1 Introduction -- 2 The PPGAFS Approach -- 2.1 Preselecting Privacy-Preserving Features -- 2.2 Generating Minimum Feature Subset Based on the Improved GA -- 3 Spam Detection and Verification Experiment Analysis -- 3.1 Web Spam Detection Procedure -- 3.2 Dataset and Evaluation Measures -- 3.3 Experiment Design and Result Analysis -- 4 Conclusion -- References -- Construction of Differentially Private Summaries Over Fully Homomorphic Encryption -- 1 Introduction -- 2 Preliminaries -- 2.1 Homomorphic Encryption -- 2.2 Differential Privacy -- 3 Related Work -- 3.1 Combination of Homomorphic Encryption and Differential Privacy -- 3.2 Range Queries Under Differential Privacy -- 4 Proposed Method -- 4.1 Overview -- 4.2 Adoption of Differential Privacy over Fully Homomorphic Encryption -- 4.3 Security Analysis -- 5 Experimental Evaluation -- 5.1 Experimental Setup -- 5.2 DP-Summary Construction Time -- 5.3 Accuracy of DP-Summary -- 6 Conclusion -- References -- SafecareOnto: A Cyber-Physical Security Ontology for Healthcare Systems -- 1 Introduction -- 2 Safecare Ontology -- 3 Knowledge Acquisition -- 4 Formalization and Implementation -- 4.1 Concepts Identification -- 4.2 Relationships Identification -- 4.3 Axioms Definition -- 4.4 Implementation -- 5 Safecare Use Cases -- 6 Related Work -- 7 Conclusion -- References.
Repurpose Image Identification for Fake News Detection -- 1 Introduction -- 2 Related Work -- 3 Proposed Framework -- 3.1 Event Type Classifier -- 3.2 Image Repurpose Detector -- 4 Experimental Evaluation -- 4.1 Experimental Datasets -- 4.2 Experiments on Event Type Classification -- 4.3 Comparative Study -- 4.4 Variants of RECAST -- 4.5 Case Study -- 5 Conclusion -- References -- Data and Information Processing -- An Urgency-Aware and Revenue-Based Itemset Placement Framework for Retail Stores -- 1 Introduction -- 2 Proposed Framework of the Problem -- 3 URIP: Urgency-Aware Itemset Placement Scheme -- 4 Performance Evaluation -- 5 Conclusion -- References -- NV-QALSH: An NVM-Optimized Implementation of Query-Aware Locality-Sensitive Hashing -- 1 Introduction -- 2 Preliminaries -- 2.1 The c-ANN Search Problem -- 2.2 The QALSH Method -- 2.3 Non-Volatile Memory -- 2.4 LB-Tree and LB-QALSH -- 3 Optimization Designs -- 3.1 Three-Level Storage Architecture -- 3.2 Leaf Node Optimization -- 3.3 Collision Counting Granularity Optimization -- 4 Experiments -- 4.1 Experiment Setup -- 4.2 Datasets and Queries -- 4.3 Evaluation Metrics -- 4.4 Benchmark Methods -- 4.5 Results and Analysis -- 5 Conclusion -- References -- NCRedis: An NVM-Optimized Redis with Memory Caching -- 1 Introduction -- 2 Implementation of NCRedis -- 2.1 Architecture of NCRedis -- 2.2 Log-Free Designs of LFSlab -- 2.3 Handling Persistent Memory Leak by LFSlab -- 2.4 Log-Free Designs of NCRedis -- 3 Evaluation -- 3.1 Experimental Setup -- 3.2 Memtier Benchmark Test -- 4 Conclusions -- References -- A Highly Modular Architecture for Canned Pattern Selection Problem -- 1 Introduction -- 2 System Architecture -- 2.1 Graph Similarity Module -- 2.2 Graph Clustering Module -- 2.3 Graph Connection Module -- 2.4 Pattern Mining Module -- 3 Conclusions -- References -- AutoEncoder for Neuroimage.
1 Introduction -- 2 The Proposed Approach -- 2.1 Variational AutoEncoder Based Regression -- 2.2 Supervised Linear Autoencoder -- 2.3 Implementation Details -- 3 Experiments -- 4 Conclusion -- References -- Knowledge Discovery -- Towards New Model for Handling Inconsistency Issues in DL-Lite Knowledge Bases -- 1 Introduction -- 2 Related Works -- 3 DL-Lite Ontology and Management of Inconsistencies: An Overview -- 4 Most-Possible Repair Proposed Approach -- 4.1 Most-Possible Repair Algorithm -- 4.2 Experimental Study and Results Analysis -- 5 Conclusion and Prospects -- References -- ContextWalk: Embedding Networks with Context Information Extracted from News Articles -- 1 Introduction -- 2 Related Work -- 3 Dataset -- 3.1 Challenges -- 4 Algorithm -- 4.1 Context Embedding -- 4.2 ContextWalk -- 4.3 Complexity -- 5 Experiments -- 5.1 Compare Clusterings -- 5.2 Network and Embedding Distances -- 6 Discussion -- References -- FIP-SHA - Finding Individual Profiles Through SHared Accounts -- 1 Introduction -- 2 Background -- 3 Related Work -- 4 FIP-SHA -- 4.1 Session Representation -- 5 Experimental Evaluation Setup and Metrics -- 6 Results -- 6.1 Cut Off Sessions -- 6.2 Clustering -- 6.3 Analysis of (Weighted) User Separation -- 6.4 Discussion -- 7 Final Considerations -- References -- A Tag-Based Transformer Community Question Answering Learning-to-Rank Model in the Home Improvement Domain -- 1 Introduction -- 2 Related Work -- 3 Task Definition -- 4 Our Approach -- 4.1 Transformer Models -- 4.2 Input and Tag Representation -- 4.3 CQA Pair Matching Model -- 4.4 Model Optimisation -- 4.5 Candidate Answers Ranking -- 5 Dataset Building and Validation -- 5.1 Subjective CQA -- 5.2 Gold Standard Definition -- 6 Evaluation -- 6.1 Experiment Setup -- 6.2 Rank-Aware Evaluation Metrics -- 6.3 Results -- 7 Conclusion -- References.
An Autonomous Crowdsourcing System -- 1 Introduction -- 2 Related Work -- 3 Crowdsourcing Task -- 3.1 Workflow -- 4 Experimental Evaluation -- 4.1 Experimental Setup -- 4.2 Results -- 5 Conclusion -- References -- Machine Learning -- The Effect of IoT Data Completeness and Correctness on Explainable Machine Learning Models -- 1 Introduction -- 2 Related Work -- 3 Method -- 4 Observation, Analysis and Validation -- 5 Conclusion -- References -- Analysis of Behavioral Facilitation Tweets for Large-Scale Natural Disasters Dataset Using Machine Learning -- 1 Introduction -- 2 Related Work -- 3 Extraction of Behavioral Facilitation Tweets -- 3.1 A Classifier Based on LSTM -- 3.2 A Classifier Based on BiLSTM -- 3.3 A Classifier Based on BERT -- 4 Experiment 1: Comparison of Models for Classification Accuracy -- 4.1 Data -- 4.2 Method -- 4.3 Result -- 5 Experiment 2: Analysis Characteristics of BF-Tweets in a Large-Scale Disaster Situation -- 5.1 Experimental Conditions -- 5.2 Results -- 5.3 Discussion -- 6 Conclusion -- References -- Using Cross Lingual Learning for Detecting Hate Speech in Portuguese -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Evaluation and Results -- 5 Final Remarks -- References -- MMEnsemble: Imbalanced Classification Framework Using Metric Learning and Multi-sampling Ratio Ensemble -- 1 Introduction -- 2 Related Work: Resampling Approaches -- 2.1 Oversampling -- 2.2 Undersampling -- 3 MMEnsemble -- 3.1 Base Ensemble Classifier - MLEnsemble -- 3.2 Ensemble Using Asset-Based Weighting -- 4 Experimental Evaluation -- 4.1 Settings -- 4.2 Results -- 4.3 Lessons Learned -- 5 Conclusion -- References -- Evaluate the Contribution of Multiple Participants in Federated Learning -- 1 Introduction -- 2 Method -- 2.1 Shapley Value for Models -- 2.2 Invalid Shapley Value -- 2.3 Method -- 2.4 Properties -- 3 Experiment.
3.1 Utility Function -- 3.2 Noisy Labels -- 4 Conclusion -- References -- DFL-Net: Effective Object Detection via Distinguishable Feature Learning -- 1 Introduction -- 2 Related Work -- 3 Design of DFL-Net -- 3.1 High-Level Idea of DFL-Net -- 3.2 Full-Scale Fusion -- 3.3 Attention Guided Feature Refinement -- 4 Performance Evaluation -- 4.1 Settings -- 4.2 Results -- 4.3 Ablation Study -- 5 Conclusion and Future Work -- References -- Transfer Learning for Larger, Broader, and Deeper Neural-Network Quantum States -- 1 Introduction -- 2 Related Work -- 3 Background -- 3.1 Quantum Many-Body Systems -- 3.2 Deep Neural-Network Quantum States -- 4 Methodology -- 5 Performance Evaluation -- 5.1 Broader Networks -- 5.2 Deeper Networks -- 6 Conclusion -- References -- LGTM: A Fast and Accurate kNN Search Algorithm in High-Dimensional Spaces -- 1 Introduction -- 2 Theoretical Motivation -- 2.1 Preliminary -- 2.2 Theoretical Foundation -- 3 LGTM: From Theory to Practice -- 3.1 Pre-processing -- 3.2 Online (Query) Processing -- 4 Experiment -- 4.1 Comparison with AKNNG -- 4.2 Comparison with State-of-the-art Algorithms -- 5 Conclusion -- References -- TSX-Means: An Optimal K Search Approach for Time Series Clustering -- 1 Introduction -- 2 Notations and Definitions -- 3 TSX-Means: A New Method for Time Series Clustering -- 3.1 Principle of the Method -- 3.2 TSX-Means Algorithm -- 4 Experimental Results -- 5 Conclusion and Perspectives -- References -- A Globally Optimal Label Selection Method via Genetic Algorithm for Multi-label Classification -- 1 Introduction -- 2 Preliminaries -- 3 The Proposed Method -- 3.1 Uninformative Label Reduction via EBMD -- 3.2 Most Informative Label Selection via GA -- 3.3 Label Selection Algorithm Combining EBMD and GA -- 4 Experiments -- 4.1 Basic Experimental Settings -- 4.2 Experimental Results and Analysis -- 5 Conclusions.
References.
Record Nr. UNISA-996464492803316
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Mobile Web and Intelligent Information Systems [[electronic resource] ] : 13th International Conference, MobiWIS 2016, Vienna, Austria, August 22-24, 2016, Proceedings / / edited by Muhammad Younas, Irfan Awan, Natalia Kryvinska, Christine Strauss, Do van Thanh
Mobile Web and Intelligent Information Systems [[electronic resource] ] : 13th International Conference, MobiWIS 2016, Vienna, Austria, August 22-24, 2016, Proceedings / / edited by Muhammad Younas, Irfan Awan, Natalia Kryvinska, Christine Strauss, Do van Thanh
Edizione [1st ed. 2016.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Descrizione fisica 1 online resource (XIV, 444 p. 147 illus.)
Disciplina 004.165
Collana Information Systems and Applications, incl. Internet/Web, and HCI
Soggetto topico Application software
Computer communication systems
User interfaces (Computer systems)
Software engineering
E-commerce
Computers and civilization
Information Systems Applications (incl. Internet)
Computer Communication Networks
User Interfaces and Human Computer Interaction
Software Engineering
e-Commerce/e-business
Computers and Society
ISBN 3-319-44215-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents -- Mobile Web - Practice and Experience -- An Android Kernel Extension to Save Energy Resources Without Impacting User Experience -- 1 Introduction -- 2 Related Work -- 3 Implementing an Energy Aware Kernel Module for Android -- 4 Evaluation -- 4.1 Experiment 1: Performance -- 4.2 Experiment 2: Battery Runtime -- 4.3 Threats to Validity -- 5 Conclusions and Future Work -- References -- Mobile Soundscape Mixer - Ready for Action -- Abstract -- 1 Introduction -- 2 System Overview -- 3 Design Process of the Mobile Soundscape Mixer Application -- 4 Guidelines and Implementation for the Mobile Soundscape Mixer Application -- 5 Performance Evaluation -- 6 Discussion -- 7 Conclusions -- Acknowledgements -- References -- Onde Chiare: A Mobile Application to Mitigate the Risk Perception from Electromagnetic Fields -- 1 Introduction -- 2 Electromagnetic Fields and Public Health -- 2.1 EMF Risk Perception -- 3 Onde Chiare: Design and Implementation -- 3.1 Use Case and Scenario -- 3.2 General Architecture -- 3.3 Server Side -- 3.4 Android App -- 4 Conclusion and Future Works -- References -- Ringtone Adaptation Based on Location and Surrounding Noise -- Abstract -- 1 Introduction -- 2 Problem Definition -- 3 New Solution -- 4 Implementation -- 5 Developed Application Testing - Solution -- 6 Conclusions -- Acknowledgement -- References -- Loop Speed Trap Data Collection Method for an Accurate Short-Term Traffic Flow Forecasting -- 1 Introduction -- 2 Cloud Based-Service for Traffic Flow Forecasting -- 3 Real-Time Data Collection Method for Traffic Flow Forecasting -- 3.1 Foreseen Arrival Time Parameter -- 3.2 Busiest Arrival Time for Safety Traffic Flow -- 4 Linear Regression for Traffic Flow Forecasting -- 5 Conclusion -- References -- Advanced Web and Mobile Systems.
Computational Thinking Through Mobile Programming -- 1 Introduction -- 2 Background -- 3 Course Description -- 3.1 Motivation and Goal -- 3.2 Rationale -- 3.3 Tools -- 3.4 Structure -- 3.5 Assessment -- 4 Case Study -- 5 Results -- 6 Conclusion and Future Work -- References -- Realistic Offloading Scheme for Mobile Cloud Computing -- Abstract -- 1 Introduction -- 2 System Design Architecture -- 2.1 Mobile Side -- 2.2 Cloud Side -- 3 Cost Prediction Models -- 3.1 Problem Formulation -- 3.2 Mobile Execution Cost Prediction -- 3.3 Cloud Execution Cost Prediction -- 4 Realistic Decision Algorithm (RDA) -- 4.1 RDA Algorithm Description -- 4.2 RDA Algorithm Overhead -- 5 Simulation Results -- 6 Related Work -- 7 Conclusion -- References -- Model Driven Development Approaches for Mobile Applications: A Survey -- 1 Introduction -- 2 Related Work -- 3 Dimensions of Analysis -- 3.1 Development Process Phases -- 3.2 Covered Mobile App Aspects -- 3.3 Model-Driven Development Techniques Applied -- 3.4 Generated Apps Perspective -- 4 Overview of MDD Approaches -- 4.1 Research Approaches -- 4.2 Commercial Solutions -- 4.3 Classification -- 5 Trends and Outlook -- 5.1 Multilevel Code Generation Approaches -- 5.2 Single Level Code Generation Approaches -- 5.3 Development Process -- 5.4 Mobile App Aspects -- 5.5 Executability -- 5.6 Native, Cross-Platform or Web Applications -- 5.7 Cross Platform Development -- 5.8 Lack of Standard Mobile Modeling Language -- 6 Conclusions -- References -- Fuzzy Ontology Based Model for Image Retrieval -- Abstract -- 1 Introduction -- 2 Related Work -- 2.1 Text Based Retrieval Systems -- 2.2 Ontology Based Retrieval Systems -- 2.3 Fuzzy Ontology Based Retrieval Systems -- 3 Proposed Methodology -- 3.1 Fuzzy Ontology Construction -- 3.2 Image Retrieval -- 3.3 Walk-Through Example -- 4 Experimental Results -- 5 Conclusion -- References.
Face-Based Difficulty Adjustment for the Game Five in a Row -- Abstract -- 1 Introduction -- 2 Problem Definition -- 2.1 Genetic Algorithms - Minimax -- 2.2 Face-Based Difficulty Adjustment of the Game According to the Shots from the Front Camera -- 3 New Solution -- 3.1 Design and Realisation of Tournament Selection -- 4 Implementation Issues of Developed Game -- 4.1 Implementation of the Game Algorithm -- 4.2 Implementation of the Technologies for the Face Recognition -- 4.3 Implementation Issues of Face-Based Difficulty Adjustment -- 4.4 Implementation Issues of Real-Time Option for Artificial Intelligence -- 5 Testing of Developed Solution -- 5.1 Testing of the Newly Designed Algorithm -- 5.2 Comparison of the Technologies for the Face Detection in the Image -- 5.3 Speed Performance Testing -- 6 Conclusions -- Acknowledgement -- References -- Security of Mobile Applications -- Adaptive Trust Scenarios for Mobile Security -- 1 Introduction -- 2 Trust in Mobile Systems -- 3 Scenarios for Adaptive Trust -- 3.1 S1: Based on System Configuration -- 3.2 S2: Communication Interface Diversity -- 3.3 S3: In Secure Environment -- 3.4 S4: In Open Environment -- 3.5 S5: Move Along Environments -- 3.6 S6: Having Connections with Many Entities -- 3.7 Applying Trust Models to the Scenarios -- 3.8 Numerical Evaluation -- 4 Conclusion -- References -- Access Control Approach in Development of Mobile Applications -- 1 Introduction -- 2 Mobile Security - Treads and Vulnerabilities -- 2.1 Security Risks in iOS Application Development -- 2.2 Major Vulnerabilities of Android Applications -- 3 Secure Development Model -- 3.1 Data Storage Security Model -- 3.2 Data Access Security Model -- 3.3 Data Transfer Security Model -- 4 Access Control Model Approach -- 5 iSec Framework as the Implementation of SDS Model -- 6 Conclusions -- References.
Using Mobile Technology in National Identity Registration -- Abstract -- 1 Introduction -- 2 Definition of Identity -- 3 The Mobile Identity Concept -- 3.1 Establishment of Citizen Identity - Birth Registration -- 3.2 Obstacles to Birth Registration in Pakistan -- 3.3 Mobile Birth Registration in Pakistan -- 4 Value Proposition -- 5 Social Benefit Analysis -- 6 Conclusion -- References -- Strengthening Mobile Network Security Using Machine Learning -- Abstract -- 1 Introduction -- 2 Related Works -- 2.1 Security Research Labs (SRLabs) -- 2.2 P1 Security -- 2.3 SBA Research -- 3 Threats and Vulnerabilities in the Mobile Network -- 4 Briefly About Machine Learning -- 5 How Can Machine Learning Improve Mobile Network Security -- 5.1 Zero Day Attacks -- 5.2 Challenges in the Construction of Conclusive Attack Signatures -- 6 Case Study: The IMSI Catcher -- 6.1 Short About IMSI Catcher -- 6.2 Challenges in the Detection of IMSI Catcher -- 6.3 Challenges in the Establishment of IMSI Catcher Signature -- 6.3.1 Handover from 3G to 2G -- 6.3.2 Location Update -- 6.3.3 Relation Between IMSI and IMEI -- 6.4 A Machine Learning Based IMSI Catcher Detection -- 7 Conclusion -- References -- Secured Authentication Using Anonymity and Password-Based Key Derivation Function -- Abstract -- 1 Introduction -- 2 Background -- 2.1 Authentication Scheme Comparison -- 2.2 Anonymity in Authentication Scheme -- 2.3 Password-Based Key Derivation Function 2 (PBKDF2) -- 3 The Proposed Scheme -- 3.1 Protocol Description -- 4 Vulnerabilities and Security Analysis -- 4.1 Cloud Vulnerabilities -- 4.2 Possible Attacks -- 5 Conclusion -- Acknowledgment -- References -- Mobile and Wireless Networking -- Optimal Resource Allocation for Non-Real Time Visible Light Communication Networks -- 1 Introduction -- 2 System Description and Problem Formulation -- 2.1 System Description.
2.2 Problem Formulation -- 2.3 Piecewise Linear Formulation -- 3 VNS Decomposition Procedure -- 4 Numerical Results -- 5 Conclusions -- References -- On Information Sharing Scheme for Automatic Evacuation Guiding System Using Evacuees' Mobile Nodes -- 1 Introduction -- 2 Related Work -- 3 Automatic Evacuation Guiding System -- 4 Proposed Scheme -- 4.1 Selection of Blocked Road Segments Based on Evacuees' Views -- 4.2 Communication Through DTN Routing -- 5 Simulation Results -- 5.1 Simulation Model -- 5.2 Appropriate Margin of View -- 5.3 Network Load -- 6 Conclusions -- References -- Cognitive Downlink Interference LTE Femtocell -- Abstract -- 1 Introduction -- 2 Related Works -- 3 Problems -- 4 Simulation -- 5 Results and Discussion -- 6 Conclusion -- References -- Correlation Properties of QOCCC Based on 1D-CCC with Parameters (N, N, 2N) and (N, N, N) -- Abstract -- 1 Introduction -- 2 CCC Definitions -- 2.1 One-Dimensional CCCs -- 2.2 Two-Dimensional CCCs -- 3 QOCCC Properties -- 3.1 Parameters -- 4 Conclusion -- Acknowledgment -- References -- Heterogeneous Traffic Modeling and Analysis for Wireless Sensor Networks -- Abstract -- 1 Introduction -- 2 Applications -- 2.1 Smart Healthcare System -- 3 Related Work -- 4 System Model and Assumptions -- 4.1 Heterogeneous Traffic Model -- 4.2 Sensor Node Queuing Model -- 5 Traffic Model of a Sensor Node -- 6 Network Performance Estimation -- 6.1 Average Loss Probability of Packet of Type k -- 6.2 Average Network Throughput of Packet of Type k -- 6.3 Average Network Delay of Packets of Type k -- 7 Network Performance -- 8 Conclusion -- References -- Duco - Hybrid Indoor Navigation -- 1 Introduction -- 2 Background -- 3 Implementation -- 3.1 Indoor Map Graph Generation -- 3.2 Initial Location Determination -- 3.3 Navigation -- 4 Evaluation -- 4.1 Evaluation Environments -- 4.2 Evaluation Hardware.
4.3 Small Environment Test - Home Scenario.
Record Nr. UNISA-996465311803316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
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Mobile Web and Intelligent Information Systems : 13th International Conference, MobiWIS 2016, Vienna, Austria, August 22-24, 2016, Proceedings / / edited by Muhammad Younas, Irfan Awan, Natalia Kryvinska, Christine Strauss, Do van Thanh
Mobile Web and Intelligent Information Systems : 13th International Conference, MobiWIS 2016, Vienna, Austria, August 22-24, 2016, Proceedings / / edited by Muhammad Younas, Irfan Awan, Natalia Kryvinska, Christine Strauss, Do van Thanh
Edizione [1st ed. 2016.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Descrizione fisica 1 online resource (XIV, 444 p. 147 illus.)
Disciplina 004.165
Collana Information Systems and Applications, incl. Internet/Web, and HCI
Soggetto topico Application software
Computer communication systems
User interfaces (Computer systems)
Software engineering
E-commerce
Computers and civilization
Information Systems Applications (incl. Internet)
Computer Communication Networks
User Interfaces and Human Computer Interaction
Software Engineering
e-Commerce/e-business
Computers and Society
ISBN 3-319-44215-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents -- Mobile Web - Practice and Experience -- An Android Kernel Extension to Save Energy Resources Without Impacting User Experience -- 1 Introduction -- 2 Related Work -- 3 Implementing an Energy Aware Kernel Module for Android -- 4 Evaluation -- 4.1 Experiment 1: Performance -- 4.2 Experiment 2: Battery Runtime -- 4.3 Threats to Validity -- 5 Conclusions and Future Work -- References -- Mobile Soundscape Mixer - Ready for Action -- Abstract -- 1 Introduction -- 2 System Overview -- 3 Design Process of the Mobile Soundscape Mixer Application -- 4 Guidelines and Implementation for the Mobile Soundscape Mixer Application -- 5 Performance Evaluation -- 6 Discussion -- 7 Conclusions -- Acknowledgements -- References -- Onde Chiare: A Mobile Application to Mitigate the Risk Perception from Electromagnetic Fields -- 1 Introduction -- 2 Electromagnetic Fields and Public Health -- 2.1 EMF Risk Perception -- 3 Onde Chiare: Design and Implementation -- 3.1 Use Case and Scenario -- 3.2 General Architecture -- 3.3 Server Side -- 3.4 Android App -- 4 Conclusion and Future Works -- References -- Ringtone Adaptation Based on Location and Surrounding Noise -- Abstract -- 1 Introduction -- 2 Problem Definition -- 3 New Solution -- 4 Implementation -- 5 Developed Application Testing - Solution -- 6 Conclusions -- Acknowledgement -- References -- Loop Speed Trap Data Collection Method for an Accurate Short-Term Traffic Flow Forecasting -- 1 Introduction -- 2 Cloud Based-Service for Traffic Flow Forecasting -- 3 Real-Time Data Collection Method for Traffic Flow Forecasting -- 3.1 Foreseen Arrival Time Parameter -- 3.2 Busiest Arrival Time for Safety Traffic Flow -- 4 Linear Regression for Traffic Flow Forecasting -- 5 Conclusion -- References -- Advanced Web and Mobile Systems.
Computational Thinking Through Mobile Programming -- 1 Introduction -- 2 Background -- 3 Course Description -- 3.1 Motivation and Goal -- 3.2 Rationale -- 3.3 Tools -- 3.4 Structure -- 3.5 Assessment -- 4 Case Study -- 5 Results -- 6 Conclusion and Future Work -- References -- Realistic Offloading Scheme for Mobile Cloud Computing -- Abstract -- 1 Introduction -- 2 System Design Architecture -- 2.1 Mobile Side -- 2.2 Cloud Side -- 3 Cost Prediction Models -- 3.1 Problem Formulation -- 3.2 Mobile Execution Cost Prediction -- 3.3 Cloud Execution Cost Prediction -- 4 Realistic Decision Algorithm (RDA) -- 4.1 RDA Algorithm Description -- 4.2 RDA Algorithm Overhead -- 5 Simulation Results -- 6 Related Work -- 7 Conclusion -- References -- Model Driven Development Approaches for Mobile Applications: A Survey -- 1 Introduction -- 2 Related Work -- 3 Dimensions of Analysis -- 3.1 Development Process Phases -- 3.2 Covered Mobile App Aspects -- 3.3 Model-Driven Development Techniques Applied -- 3.4 Generated Apps Perspective -- 4 Overview of MDD Approaches -- 4.1 Research Approaches -- 4.2 Commercial Solutions -- 4.3 Classification -- 5 Trends and Outlook -- 5.1 Multilevel Code Generation Approaches -- 5.2 Single Level Code Generation Approaches -- 5.3 Development Process -- 5.4 Mobile App Aspects -- 5.5 Executability -- 5.6 Native, Cross-Platform or Web Applications -- 5.7 Cross Platform Development -- 5.8 Lack of Standard Mobile Modeling Language -- 6 Conclusions -- References -- Fuzzy Ontology Based Model for Image Retrieval -- Abstract -- 1 Introduction -- 2 Related Work -- 2.1 Text Based Retrieval Systems -- 2.2 Ontology Based Retrieval Systems -- 2.3 Fuzzy Ontology Based Retrieval Systems -- 3 Proposed Methodology -- 3.1 Fuzzy Ontology Construction -- 3.2 Image Retrieval -- 3.3 Walk-Through Example -- 4 Experimental Results -- 5 Conclusion -- References.
Face-Based Difficulty Adjustment for the Game Five in a Row -- Abstract -- 1 Introduction -- 2 Problem Definition -- 2.1 Genetic Algorithms - Minimax -- 2.2 Face-Based Difficulty Adjustment of the Game According to the Shots from the Front Camera -- 3 New Solution -- 3.1 Design and Realisation of Tournament Selection -- 4 Implementation Issues of Developed Game -- 4.1 Implementation of the Game Algorithm -- 4.2 Implementation of the Technologies for the Face Recognition -- 4.3 Implementation Issues of Face-Based Difficulty Adjustment -- 4.4 Implementation Issues of Real-Time Option for Artificial Intelligence -- 5 Testing of Developed Solution -- 5.1 Testing of the Newly Designed Algorithm -- 5.2 Comparison of the Technologies for the Face Detection in the Image -- 5.3 Speed Performance Testing -- 6 Conclusions -- Acknowledgement -- References -- Security of Mobile Applications -- Adaptive Trust Scenarios for Mobile Security -- 1 Introduction -- 2 Trust in Mobile Systems -- 3 Scenarios for Adaptive Trust -- 3.1 S1: Based on System Configuration -- 3.2 S2: Communication Interface Diversity -- 3.3 S3: In Secure Environment -- 3.4 S4: In Open Environment -- 3.5 S5: Move Along Environments -- 3.6 S6: Having Connections with Many Entities -- 3.7 Applying Trust Models to the Scenarios -- 3.8 Numerical Evaluation -- 4 Conclusion -- References -- Access Control Approach in Development of Mobile Applications -- 1 Introduction -- 2 Mobile Security - Treads and Vulnerabilities -- 2.1 Security Risks in iOS Application Development -- 2.2 Major Vulnerabilities of Android Applications -- 3 Secure Development Model -- 3.1 Data Storage Security Model -- 3.2 Data Access Security Model -- 3.3 Data Transfer Security Model -- 4 Access Control Model Approach -- 5 iSec Framework as the Implementation of SDS Model -- 6 Conclusions -- References.
Using Mobile Technology in National Identity Registration -- Abstract -- 1 Introduction -- 2 Definition of Identity -- 3 The Mobile Identity Concept -- 3.1 Establishment of Citizen Identity - Birth Registration -- 3.2 Obstacles to Birth Registration in Pakistan -- 3.3 Mobile Birth Registration in Pakistan -- 4 Value Proposition -- 5 Social Benefit Analysis -- 6 Conclusion -- References -- Strengthening Mobile Network Security Using Machine Learning -- Abstract -- 1 Introduction -- 2 Related Works -- 2.1 Security Research Labs (SRLabs) -- 2.2 P1 Security -- 2.3 SBA Research -- 3 Threats and Vulnerabilities in the Mobile Network -- 4 Briefly About Machine Learning -- 5 How Can Machine Learning Improve Mobile Network Security -- 5.1 Zero Day Attacks -- 5.2 Challenges in the Construction of Conclusive Attack Signatures -- 6 Case Study: The IMSI Catcher -- 6.1 Short About IMSI Catcher -- 6.2 Challenges in the Detection of IMSI Catcher -- 6.3 Challenges in the Establishment of IMSI Catcher Signature -- 6.3.1 Handover from 3G to 2G -- 6.3.2 Location Update -- 6.3.3 Relation Between IMSI and IMEI -- 6.4 A Machine Learning Based IMSI Catcher Detection -- 7 Conclusion -- References -- Secured Authentication Using Anonymity and Password-Based Key Derivation Function -- Abstract -- 1 Introduction -- 2 Background -- 2.1 Authentication Scheme Comparison -- 2.2 Anonymity in Authentication Scheme -- 2.3 Password-Based Key Derivation Function 2 (PBKDF2) -- 3 The Proposed Scheme -- 3.1 Protocol Description -- 4 Vulnerabilities and Security Analysis -- 4.1 Cloud Vulnerabilities -- 4.2 Possible Attacks -- 5 Conclusion -- Acknowledgment -- References -- Mobile and Wireless Networking -- Optimal Resource Allocation for Non-Real Time Visible Light Communication Networks -- 1 Introduction -- 2 System Description and Problem Formulation -- 2.1 System Description.
2.2 Problem Formulation -- 2.3 Piecewise Linear Formulation -- 3 VNS Decomposition Procedure -- 4 Numerical Results -- 5 Conclusions -- References -- On Information Sharing Scheme for Automatic Evacuation Guiding System Using Evacuees' Mobile Nodes -- 1 Introduction -- 2 Related Work -- 3 Automatic Evacuation Guiding System -- 4 Proposed Scheme -- 4.1 Selection of Blocked Road Segments Based on Evacuees' Views -- 4.2 Communication Through DTN Routing -- 5 Simulation Results -- 5.1 Simulation Model -- 5.2 Appropriate Margin of View -- 5.3 Network Load -- 6 Conclusions -- References -- Cognitive Downlink Interference LTE Femtocell -- Abstract -- 1 Introduction -- 2 Related Works -- 3 Problems -- 4 Simulation -- 5 Results and Discussion -- 6 Conclusion -- References -- Correlation Properties of QOCCC Based on 1D-CCC with Parameters (N, N, 2N) and (N, N, N) -- Abstract -- 1 Introduction -- 2 CCC Definitions -- 2.1 One-Dimensional CCCs -- 2.2 Two-Dimensional CCCs -- 3 QOCCC Properties -- 3.1 Parameters -- 4 Conclusion -- Acknowledgment -- References -- Heterogeneous Traffic Modeling and Analysis for Wireless Sensor Networks -- Abstract -- 1 Introduction -- 2 Applications -- 2.1 Smart Healthcare System -- 3 Related Work -- 4 System Model and Assumptions -- 4.1 Heterogeneous Traffic Model -- 4.2 Sensor Node Queuing Model -- 5 Traffic Model of a Sensor Node -- 6 Network Performance Estimation -- 6.1 Average Loss Probability of Packet of Type k -- 6.2 Average Network Throughput of Packet of Type k -- 6.3 Average Network Delay of Packets of Type k -- 7 Network Performance -- 8 Conclusion -- References -- Duco - Hybrid Indoor Navigation -- 1 Introduction -- 2 Background -- 3 Implementation -- 3.1 Indoor Map Graph Generation -- 3.2 Initial Location Determination -- 3.3 Navigation -- 4 Evaluation -- 4.1 Evaluation Environments -- 4.2 Evaluation Hardware.
4.3 Small Environment Test - Home Scenario.
Record Nr. UNINA-9910484996103321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
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