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Big Data Analytics [[electronic resource] ] : 7th International Conference, BDA 2019, Ahmedabad, India, December 17–20, 2019, Proceedings / / edited by Sanjay Madria, Philippe Fournier-Viger, Sanjay Chaudhary, P. Krishna Reddy
| Big Data Analytics [[electronic resource] ] : 7th International Conference, BDA 2019, Ahmedabad, India, December 17–20, 2019, Proceedings / / edited by Sanjay Madria, Philippe Fournier-Viger, Sanjay Chaudhary, P. Krishna Reddy |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (466 pages) |
| Disciplina | 005.7 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico |
Data mining
Artificial intelligence Application software Database management Data Mining and Knowledge Discovery Artificial Intelligence Information Systems Applications (incl. Internet) Database Management |
| ISBN | 3-030-37188-3 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Big Data Analytics: Vision and Perspectives -- Transforming Sensing Data into Smart Data for Smart Sustainable Cities -- Deep Learning Models for Medical Image Analysis: Challenges and Future Directions -- Recent Advances and Challenges in design of Non-Goal Oriented Dialogue System -- Data Cube is Dead, Long Life to Data Cube in the Age of Web Data -- Search and Information Extraction -- Improving Result Diversity using Query Term Proximity in Exploratory Search -- Segment-search vs Knowledge Graphs: Making a Keyword Search Engine for Web Documents -- Pairing Users in Social Media via Processing Meta-data from Conversational Files -- Large-Scale Information Extraction from Emails with Data Constraints -- Comparative Analysis of Rule-based, Dictionary-based and Hybrid Stemmers for Gujarati Language -- Predictive Analytics in Medical and Agricultural Domains -- Artificial Intelligence and Bayesian Knowledge Network in Health Care – Smartphone Apps for diagnosis and differentiation of anemias with higher accuracy at Resource Constrained Point-of-Care settings -- Analyzing Domain Knowledge for Big Data Analysis: A Case Study with Urban Tree Type Classification -- Market Intelligence for Agricultural Commodities using Forecasting and Deep Learning Techniques -- Graph Analytics -- TKG: Efficient Mining of Top-K Frequent Subgraphs -- Why Multilayer Networks Instead Of Simple Graphs? Modeling Effectiveness And Analysis Flexibility & Efficiency! -- Gossip Based Distributed Real Time Task Scheduling with Guaranteed Performance on Heterogeneous Networks -- Data-Driven Optimization of Public Transit Schedule -- Pattern Mining -- Discovering Spatial High Utility Frequent Itemsets in Spatiotemporal Databases -- Efficient Algorithms For Flock Detection in Large Spatio-Temporal Data -- Local Temporal Compression for (Globally) Evolving Spatial Surfaces -- An Explicit Relationship between Sequential Patterns and their Concise Representations -- Machine Learning -- A novel approach to identify the determinants of online review helpfulness and predict the helpfulness score across product categories -- Analysis and Recognition of Hand-drawn Images with Effective Data Handling -- Real Time Static Gesture Detection Using Deep Learning -- Interpreting Context of Images using Scene Graphs -- Deep Learning in the Domain of Near-Duplicate Document Detection. |
| Record Nr. | UNISA-996466188103316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Big Data Analytics : 7th International Conference, BDA 2019, Ahmedabad, India, December 17–20, 2019, Proceedings / / edited by Sanjay Madria, Philippe Fournier-Viger, Sanjay Chaudhary, P. Krishna Reddy
| Big Data Analytics : 7th International Conference, BDA 2019, Ahmedabad, India, December 17–20, 2019, Proceedings / / edited by Sanjay Madria, Philippe Fournier-Viger, Sanjay Chaudhary, P. Krishna Reddy |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (466 pages) |
| Disciplina |
005.7
006.312 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico |
Data mining
Artificial intelligence Application software Database management Data Mining and Knowledge Discovery Artificial Intelligence Information Systems Applications (incl. Internet) Database Management |
| ISBN | 3-030-37188-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Big Data Analytics: Vision and Perspectives -- Transforming Sensing Data into Smart Data for Smart Sustainable Cities -- Deep Learning Models for Medical Image Analysis: Challenges and Future Directions -- Recent Advances and Challenges in design of Non-Goal Oriented Dialogue System -- Data Cube is Dead, Long Life to Data Cube in the Age of Web Data -- Search and Information Extraction -- Improving Result Diversity using Query Term Proximity in Exploratory Search -- Segment-search vs Knowledge Graphs: Making a Keyword Search Engine for Web Documents -- Pairing Users in Social Media via Processing Meta-data from Conversational Files -- Large-Scale Information Extraction from Emails with Data Constraints -- Comparative Analysis of Rule-based, Dictionary-based and Hybrid Stemmers for Gujarati Language -- Predictive Analytics in Medical and Agricultural Domains -- Artificial Intelligence and Bayesian Knowledge Network in Health Care – Smartphone Apps for diagnosis and differentiation of anemias with higher accuracy at Resource Constrained Point-of-Care settings -- Analyzing Domain Knowledge for Big Data Analysis: A Case Study with Urban Tree Type Classification -- Market Intelligence for Agricultural Commodities using Forecasting and Deep Learning Techniques -- Graph Analytics -- TKG: Efficient Mining of Top-K Frequent Subgraphs -- Why Multilayer Networks Instead Of Simple Graphs? Modeling Effectiveness And Analysis Flexibility & Efficiency! -- Gossip Based Distributed Real Time Task Scheduling with Guaranteed Performance on Heterogeneous Networks -- Data-Driven Optimization of Public Transit Schedule -- Pattern Mining -- Discovering Spatial High Utility Frequent Itemsets in Spatiotemporal Databases -- Efficient Algorithms For Flock Detection in Large Spatio-Temporal Data -- Local Temporal Compression for (Globally) Evolving Spatial Surfaces -- An Explicit Relationship between Sequential Patterns and their Concise Representations -- Machine Learning -- A novel approach to identify the determinants of online review helpfulness and predict the helpfulness score across product categories -- Analysis and Recognition of Hand-drawn Images with Effective Data Handling -- Real Time Static Gesture Detection Using Deep Learning -- Interpreting Context of Images using Scene Graphs -- Deep Learning in the Domain of Near-Duplicate Document Detection. |
| Record Nr. | UNINA-9910364954403321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Big Data Analytics [[electronic resource] ] : 6th International Conference, BDA 2018, Warangal, India, December 18–21, 2018, Proceedings / / edited by Anirban Mondal, Himanshu Gupta, Jaideep Srivastava, P. Krishna Reddy, D.V.L.N. Somayajulu
| Big Data Analytics [[electronic resource] ] : 6th International Conference, BDA 2018, Warangal, India, December 18–21, 2018, Proceedings / / edited by Anirban Mondal, Himanshu Gupta, Jaideep Srivastava, P. Krishna Reddy, D.V.L.N. Somayajulu |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XV, 424 p. 185 illus., 139 illus. in color.) |
| Disciplina | 005.7 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico |
Data mining
Artificial intelligence Database management Application software Computer system failures Mathematical logic Data Mining and Knowledge Discovery Artificial Intelligence Database Management Information Systems Applications (incl. Internet) System Performance and Evaluation Mathematical Logic and Formal Languages |
| ISBN | 3-030-04780-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Big Data Analytics: Vision and Perspectives -- Financial Data Analytics and Data Streams -- Web and Social Media Data -- Big Data Systems and Frameworks -- Predictive Analytics in Healthcare and Agricultural Domains -- Machine Learning and Pattern Mining. |
| Record Nr. | UNISA-996466306703316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Big Data Analytics : 6th International Conference, BDA 2018, Warangal, India, December 18–21, 2018, Proceedings / / edited by Anirban Mondal, Himanshu Gupta, Jaideep Srivastava, P. Krishna Reddy, D.V.L.N. Somayajulu
| Big Data Analytics : 6th International Conference, BDA 2018, Warangal, India, December 18–21, 2018, Proceedings / / edited by Anirban Mondal, Himanshu Gupta, Jaideep Srivastava, P. Krishna Reddy, D.V.L.N. Somayajulu |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XV, 424 p. 185 illus., 139 illus. in color.) |
| Disciplina |
005.7
006.312 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico |
Data mining
Artificial intelligence Database management Application software Computer system failures Mathematical logic Data Mining and Knowledge Discovery Artificial Intelligence Database Management Information Systems Applications (incl. Internet) System Performance and Evaluation Mathematical Logic and Formal Languages |
| ISBN | 3-030-04780-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Big Data Analytics: Vision and Perspectives -- Financial Data Analytics and Data Streams -- Web and Social Media Data -- Big Data Systems and Frameworks -- Predictive Analytics in Healthcare and Agricultural Domains -- Machine Learning and Pattern Mining. |
| Record Nr. | UNINA-9910349387703321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Big Data Analytics [[electronic resource] ] : 5th International Conference, BDA 2017, Hyderabad, India, December 12-15, 2017, Proceedings / / edited by P. Krishna Reddy, Ashish Sureka, Sharma Chakravarthy, Subhash Bhalla
| Big Data Analytics [[electronic resource] ] : 5th International Conference, BDA 2017, Hyderabad, India, December 12-15, 2017, Proceedings / / edited by P. Krishna Reddy, Ashish Sureka, Sharma Chakravarthy, Subhash Bhalla |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XII, 311 p. 112 illus.) |
| Disciplina | 005.7 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico |
Data mining
Database management Application software Artificial intelligence Computer communication systems Data Mining and Knowledge Discovery Database Management Information Systems Applications (incl. Internet) Artificial Intelligence Computer Communication Networks |
| ISBN | 3-319-72413-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Big data analytics -- Information and knowledge management -- Mining of massive datasets -- Computational modeling -- Data mining and analysis. |
| Record Nr. | UNISA-996466423303316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Big Data Analytics : 5th International Conference, BDA 2017, Hyderabad, India, December 12-15, 2017, Proceedings / / edited by P. Krishna Reddy, Ashish Sureka, Sharma Chakravarthy, Subhash Bhalla
| Big Data Analytics : 5th International Conference, BDA 2017, Hyderabad, India, December 12-15, 2017, Proceedings / / edited by P. Krishna Reddy, Ashish Sureka, Sharma Chakravarthy, Subhash Bhalla |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XII, 311 p. 112 illus.) |
| Disciplina | 005.7 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico |
Data mining
Database management Application software Artificial intelligence Computer communication systems Data Mining and Knowledge Discovery Database Management Information Systems Applications (incl. Internet) Artificial Intelligence Computer Communication Networks |
| ISBN | 3-319-72413-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Big data analytics -- Information and knowledge management -- Mining of massive datasets -- Computational modeling -- Data mining and analysis. |
| Record Nr. | UNINA-9910484640303321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Database Systems for Advanced Applications : DASFAA 2022 International Workshops : BDMS, BDQM, GDMA, IWBT, MAQTDS, and PMBD, Virtual event, April 11-14, 2022, proceedings / / edited by Uday Kiran Rage, Vikram Goyal, P. Krishna Reddy
| Database Systems for Advanced Applications : DASFAA 2022 International Workshops : BDMS, BDQM, GDMA, IWBT, MAQTDS, and PMBD, Virtual event, April 11-14, 2022, proceedings / / edited by Uday Kiran Rage, Vikram Goyal, P. Krishna Reddy |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (446 pages) |
| Disciplina | 943.005 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico | Database management |
| ISBN | 3-031-11217-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- PMDB -- An Algorithm for Mining Fixed-Length High Utility Itemsets -- 1 Introduction -- 2 Background -- 2.1 Problem Description and Definitions -- 2.2 Related Work -- 3 Algorithm HUIKM -- 3.1 Create a Tree and a Header Table -- 3.2 Ming HUIK from a Tree -- 4 Experimental Results -- 5 Conclusion -- References -- A Novel Method to Create Synthetic Samples with Autoencoder Multi-layer Extreme Learning Machine -- 1 Introduction -- 2 SMOTE Method -- 3 Proposed AE-MLELM-SynMin Method -- 3.1 Training AE-MLELM -- 3.2 Conducting Crossover and Mutation Operations -- 3.3 Creating Synthetic Samples -- 4 Experiments -- 4.1 Experiment Setting -- 4.2 Information Amount Analysis of SMOTE and AE-MLELM-SynMin -- 4.3 Comparison Among AE-MLELM-SynMin, SMOTE, Borderline-SMOTE, Random-SMOTE, and SMOTE-IPF -- 5 Conclusion -- References -- Pattern Mining: Current Challenges and Opportunities -- 1 Introduction -- 2 C1: Mining Patterns in Complex Graph Data -- 3 C2: Targeted Pattern Mining -- 4 C3: Repetitive Sequential Pattern Mining -- 5 C4: Incremental, Stream and Interactive Pattern Mining -- 6 C5: Heuristic Pattern Mining -- 7 C6: Mining Interesting Patterns -- 8 Conclusion -- References -- Why Not to Trust Big Data: Discussing Statistical Paradoxes -- 1 Introduction -- 2 Why Not to Trust on Data Science, AI, ML and Big Data -- 3 Statistical Paradoxes -- 3.1 Berkson Paradox -- 3.2 Yule-Simpson's Paradox -- 4 Existence of Simpson's Paradox in Big Data -- 4.1 Datasets -- 5 Analysis Simpson's Paradox in Real Life: A Case Study -- 5.1 The Dataset -- 5.2 Data Analysis -- 6 Discussion -- 7 Conclusion -- References -- Localized Metric Learning for Large Multi-class Extremely Imbalanced Face Database -- 1 Introduction -- 2 Metric Learning as an Antidote for the Class Imbalance Problem.
3 Localized Metric Learning - The Proposed Approach -- 3.1 Division of Dataset Into Subsets -- 3.2 Localized Metric Learning -- 3.3 Algorithm -- 4 Results and Discussions -- 5 Conclusions -- References -- Top-k Dominating Queries on Incremental Datasets -- 1 Introduction -- 2 Literature Review -- 2.1 Top-k Dominance Query -- 2.2 Dynamic Update of Data Mining -- 3 Query Base Preparation -- 4 Algorithm Description -- 5 Experiment and Analysis -- 6 Conclusion -- References -- IWBT -- Collaborative Blockchain Based Distributed Denial of Service Attack Mitigation Approach with IP Reputation System -- 1 Introduction -- 2 Theoretical Background -- 2.1 Blockchain Technology - Brief -- 2.2 Overview of DDoS Mitigation Approaches and Techniques -- 2.3 IP Reputation Scheme -- 3 Problem Description -- 4 Related Work -- 5 Research Questions -- 6 Approach and Next Step -- 6.1 Proposed Architecture -- 6.2 Integration of IP Reputation System with Proposed Architecture -- 6.3 Implementation Strategy -- 6.4 Advantages of Proposed System Over Existing Implementation -- 7 Conclusion -- References -- Model-Driven Development of Distributed Ledger Applications -- 1 Introduction -- 1.1 Running Example -- 2 Background -- 2.1 Distributed Ledger Technology and Hybrid DLT/DB Applications -- 2.2 MDD with the Interaction Flow Modeling Language -- 3 Development of Hybrid DLT/DB Applications -- 3.1 Requirement Specification -- 3.2 Data Design -- 3.3 Interface Design -- 3.4 Operation Design -- 3.5 Architecture Design -- 4 Implementation -- 5 Related Work -- 6 Conclusion -- References -- Towards a Blockchain Solution for Customs Duty-Related Fraud -- 1 Introduction -- 2 Related Literature -- 3 Types of Blockchains for Customs Enforcement -- 4 Hyperledger Fabric -- 4.1 Transaction Overview -- 4.2 Ensuring Transaction Order. 5 Detecting and Mitigating Customs Duty Fraud Using Fabric: Three Scenarios -- 5.1 Underreporting the Cargo Weight or Quantity -- 5.2 Relying on a Bill of Lading for Customs Audits -- 5.3 Misrepresenting the Country of Origin: Shipping Goods to an Intermediate Country to Avoid Import Tariffs -- 6 Benchmarking Scalability -- 6.1 Benchmarking Setup -- 6.2 Performance Benchmarking Results and Analysis -- 7 Other Implementation Considerations -- 8 Conclusion -- References -- Securing Cookies/Sessions Through Non-fungible Tokens -- 1 Introduction -- 2 Background -- 3 Literature Review -- 3.1 Blockchain -- 3.2 Cookies -- 4 The Proposed Model -- 4.1 Properties -- 4.2 Preliminaries -- 4.3 Model Description -- 5 Security Analysis and Discussion -- 6 Conclusions and Future Works -- References -- GDMA -- Chinese Spelling Error Detection and Correction Based on Knowledge Graph -- 1 Introduction -- 2 Model -- 2.1 Knowledge Network -- 2.2 Detection and Correction Network -- 2.3 Filter -- 2.4 Loss -- 3 Experiments and Evaluation -- 3.1 Datasets and Baseline -- 3.2 Evaluation -- 3.3 Results -- 4 Related Work -- 5 Conclusion -- References -- Construction and Application of Event Logic Graph: A Survey -- 1 Introduction -- 2 Event Extraction -- 2.1 Methods Based on Pattern Matching -- 2.2 Methods Based on Machine Learning -- 2.3 Methods Based on Deep Learning -- 3 Event Relation Extraction -- 4 Applications -- 4.1 Detect Hot Events -- 4.2 Analyze the Event Lineage -- 4.3 Predict Future Events -- 5 Summary and Prospect -- References -- Enhancing Low-Resource Languages Question Answering with Syntactic Graph -- 1 Introduction -- 2 Syntactic Information Evolvement in mBERT -- 3 Related Work -- 4 Method -- 4.1 Syntactic Graph -- 4.2 Syntactic Graph Prediction Task -- 5 Experiment -- 5.1 Datasets and Baseline Models -- 5.2 Setup and Evaluation Metric. 5.3 Experiment Results -- 6 Analysis -- 6.1 Why Use Parallel Sentence Pairs to Train Syntax Task? -- 6.2 Why the Syntactic Graph Prediction Task Works? -- 7 Conclusions -- References -- Profile Consistency Discrimination -- 1 Introduction -- 2 Relate Work -- 2.1 Natural Language Inference -- 2.2 Role Consistency -- 3 Consistency Discrimination -- 3.1 Problem Definition -- 3.2 Consistency Discriminator -- 4 Experiments Setup -- 4.1 Implementation Details and Evaluations -- 4.2 Baselines -- 5 Result -- 6 Case Study -- 7 Conclusion and Future Work -- References -- BDMS -- H-V: An Improved Coding Layout Based on Erasure Coded Storage System -- 1 Introduction -- 2 Related Work -- 3 HRS(n,k) - VRS(n',k') Encoding Method -- 4 Effect Analysis of HRS(n,k) - VRS(n',k') -- 4.1 Data Transmission Performance Analysis -- 4.2 Storage Redundancy Analysis -- 5 Conclusion -- References -- Astral: An Autoencoder-Based Model for Pedestrian Trajectory Prediction of Variable-Length -- 1 Introduction -- 2 Problem Definitions -- 3 Methodology -- 3.1 Model Framework -- 3.2 Autoencoder -- 3.3 Multi-head Attention -- 3.4 Online Model -- 4 Experiments -- 4.1 Experimental Settings -- 4.2 Evaluation of Trajectory Prediction -- 4.3 Ablation Studies -- 4.4 Case Study -- 5 Related Work -- 5.1 Crowd Interaction -- 5.2 LSTM for Sequence Prediction -- 6 Conclusion -- References -- A Survey on Spatiotemporal Data Processing Techniques in Smart Urban Rail -- 1 Introduction -- 2 Spatiotemporal Data Processing Technology -- 3 Applications of Smart Urban Rail -- 3.1 Intelligent Scheduling -- 3.2 Intelligent Operation Platform -- 3.3 Intelligent Perception -- 3.4 Intelligent Train Control -- 4 Future Work -- 5 Conclusion -- References -- Fast Vehicle Track Counting in Traffic Video -- 1 Introduction -- 2 Related Work -- 3 Preliminary and Problem Statement. 4 An Efficient Vehicle Query Counting Method -- 4.1 Adaptively Choosing Frames for Vehicle Detection -- 4.2 Vehicle Tracking Based on Location and Simple Appearance Features -- 4.3 Cascade Track Judgment and Counting -- 5 Experiments -- 5.1 Settings -- 5.2 Metrics -- 5.3 Experimental Results -- 5.4 Ablation Experiments -- 6 Conclusion -- References -- TSummary: A Traffic Summarization System Using Semantic Words -- 1 Introduction -- 2 System Overview -- 2.1 Feature Extraction -- 2.2 Preliminary Concepts -- 2.3 Structure of TSummary -- 3 Traffic Summarization -- 3.1 Periodic Feature Detection -- 3.2 Road Partitioning -- 3.3 Temporal Merge -- 4 Experiment -- 4.1 Experiment Setup -- 4.2 Evaluation Approach -- 4.3 Performance Evaluation -- 5 Related Work -- 6 Conclusions -- References -- Attention-Cooperated Reinforcement Learning for Multi-agent Path Planning -- 1 Introduction -- 2 Related Work -- 2.1 Classical Path Planning Methods -- 2.2 Learning Based Methods -- 3 Problem Formulation -- 4 Approach -- 4.1 State's Structure -- 4.2 Action Space -- 4.3 Reward Design -- 4.4 Model Architecture -- 5 Experiments -- 5.1 Experiment Setting -- 5.2 Training Details -- 5.3 Metrics -- 5.4 Baselines -- 5.5 Results -- 6 Conclusion -- References -- Big Data-Driven Stable Task Allocation in Ride-Hailing Services -- 1 Introduction -- 2 Related Work -- 3 Problem Definition -- 3.1 Preliminaries and Definition -- 3.2 A Baseline Approach -- 4 Equilibrium Stable Matching and Global Distance Optimization -- 4.1 Chain Algorithm -- 4.2 The Benefit Function for Equilibrium -- 5 Experimental Study -- 6 Conclusion -- References -- Weighted Mean-Field Multi-Agent Reinforcement Learning via Reward Attribution Decomposition -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 3.1 Markov Decision Process and Markov Game -- 3.2 Mean-Field Reinforcement Learning -- 4 Algorithm. 4.1 Weighted Mean-Field Approximation. |
| Record Nr. | UNINA-9910584480803321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Database Systems for Advanced Applications : DASFAA 2022 International Workshops : BDMS, BDQM, GDMA, IWBT, MAQTDS, and PMBD, Virtual event, April 11-14, 2022, proceedings / / edited by Uday Kiran Rage, Vikram Goyal, P. Krishna Reddy
| Database Systems for Advanced Applications : DASFAA 2022 International Workshops : BDMS, BDQM, GDMA, IWBT, MAQTDS, and PMBD, Virtual event, April 11-14, 2022, proceedings / / edited by Uday Kiran Rage, Vikram Goyal, P. Krishna Reddy |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (446 pages) |
| Disciplina | 943.005 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico | Database management |
| ISBN | 3-031-11217-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- PMDB -- An Algorithm for Mining Fixed-Length High Utility Itemsets -- 1 Introduction -- 2 Background -- 2.1 Problem Description and Definitions -- 2.2 Related Work -- 3 Algorithm HUIKM -- 3.1 Create a Tree and a Header Table -- 3.2 Ming HUIK from a Tree -- 4 Experimental Results -- 5 Conclusion -- References -- A Novel Method to Create Synthetic Samples with Autoencoder Multi-layer Extreme Learning Machine -- 1 Introduction -- 2 SMOTE Method -- 3 Proposed AE-MLELM-SynMin Method -- 3.1 Training AE-MLELM -- 3.2 Conducting Crossover and Mutation Operations -- 3.3 Creating Synthetic Samples -- 4 Experiments -- 4.1 Experiment Setting -- 4.2 Information Amount Analysis of SMOTE and AE-MLELM-SynMin -- 4.3 Comparison Among AE-MLELM-SynMin, SMOTE, Borderline-SMOTE, Random-SMOTE, and SMOTE-IPF -- 5 Conclusion -- References -- Pattern Mining: Current Challenges and Opportunities -- 1 Introduction -- 2 C1: Mining Patterns in Complex Graph Data -- 3 C2: Targeted Pattern Mining -- 4 C3: Repetitive Sequential Pattern Mining -- 5 C4: Incremental, Stream and Interactive Pattern Mining -- 6 C5: Heuristic Pattern Mining -- 7 C6: Mining Interesting Patterns -- 8 Conclusion -- References -- Why Not to Trust Big Data: Discussing Statistical Paradoxes -- 1 Introduction -- 2 Why Not to Trust on Data Science, AI, ML and Big Data -- 3 Statistical Paradoxes -- 3.1 Berkson Paradox -- 3.2 Yule-Simpson's Paradox -- 4 Existence of Simpson's Paradox in Big Data -- 4.1 Datasets -- 5 Analysis Simpson's Paradox in Real Life: A Case Study -- 5.1 The Dataset -- 5.2 Data Analysis -- 6 Discussion -- 7 Conclusion -- References -- Localized Metric Learning for Large Multi-class Extremely Imbalanced Face Database -- 1 Introduction -- 2 Metric Learning as an Antidote for the Class Imbalance Problem.
3 Localized Metric Learning - The Proposed Approach -- 3.1 Division of Dataset Into Subsets -- 3.2 Localized Metric Learning -- 3.3 Algorithm -- 4 Results and Discussions -- 5 Conclusions -- References -- Top-k Dominating Queries on Incremental Datasets -- 1 Introduction -- 2 Literature Review -- 2.1 Top-k Dominance Query -- 2.2 Dynamic Update of Data Mining -- 3 Query Base Preparation -- 4 Algorithm Description -- 5 Experiment and Analysis -- 6 Conclusion -- References -- IWBT -- Collaborative Blockchain Based Distributed Denial of Service Attack Mitigation Approach with IP Reputation System -- 1 Introduction -- 2 Theoretical Background -- 2.1 Blockchain Technology - Brief -- 2.2 Overview of DDoS Mitigation Approaches and Techniques -- 2.3 IP Reputation Scheme -- 3 Problem Description -- 4 Related Work -- 5 Research Questions -- 6 Approach and Next Step -- 6.1 Proposed Architecture -- 6.2 Integration of IP Reputation System with Proposed Architecture -- 6.3 Implementation Strategy -- 6.4 Advantages of Proposed System Over Existing Implementation -- 7 Conclusion -- References -- Model-Driven Development of Distributed Ledger Applications -- 1 Introduction -- 1.1 Running Example -- 2 Background -- 2.1 Distributed Ledger Technology and Hybrid DLT/DB Applications -- 2.2 MDD with the Interaction Flow Modeling Language -- 3 Development of Hybrid DLT/DB Applications -- 3.1 Requirement Specification -- 3.2 Data Design -- 3.3 Interface Design -- 3.4 Operation Design -- 3.5 Architecture Design -- 4 Implementation -- 5 Related Work -- 6 Conclusion -- References -- Towards a Blockchain Solution for Customs Duty-Related Fraud -- 1 Introduction -- 2 Related Literature -- 3 Types of Blockchains for Customs Enforcement -- 4 Hyperledger Fabric -- 4.1 Transaction Overview -- 4.2 Ensuring Transaction Order. 5 Detecting and Mitigating Customs Duty Fraud Using Fabric: Three Scenarios -- 5.1 Underreporting the Cargo Weight or Quantity -- 5.2 Relying on a Bill of Lading for Customs Audits -- 5.3 Misrepresenting the Country of Origin: Shipping Goods to an Intermediate Country to Avoid Import Tariffs -- 6 Benchmarking Scalability -- 6.1 Benchmarking Setup -- 6.2 Performance Benchmarking Results and Analysis -- 7 Other Implementation Considerations -- 8 Conclusion -- References -- Securing Cookies/Sessions Through Non-fungible Tokens -- 1 Introduction -- 2 Background -- 3 Literature Review -- 3.1 Blockchain -- 3.2 Cookies -- 4 The Proposed Model -- 4.1 Properties -- 4.2 Preliminaries -- 4.3 Model Description -- 5 Security Analysis and Discussion -- 6 Conclusions and Future Works -- References -- GDMA -- Chinese Spelling Error Detection and Correction Based on Knowledge Graph -- 1 Introduction -- 2 Model -- 2.1 Knowledge Network -- 2.2 Detection and Correction Network -- 2.3 Filter -- 2.4 Loss -- 3 Experiments and Evaluation -- 3.1 Datasets and Baseline -- 3.2 Evaluation -- 3.3 Results -- 4 Related Work -- 5 Conclusion -- References -- Construction and Application of Event Logic Graph: A Survey -- 1 Introduction -- 2 Event Extraction -- 2.1 Methods Based on Pattern Matching -- 2.2 Methods Based on Machine Learning -- 2.3 Methods Based on Deep Learning -- 3 Event Relation Extraction -- 4 Applications -- 4.1 Detect Hot Events -- 4.2 Analyze the Event Lineage -- 4.3 Predict Future Events -- 5 Summary and Prospect -- References -- Enhancing Low-Resource Languages Question Answering with Syntactic Graph -- 1 Introduction -- 2 Syntactic Information Evolvement in mBERT -- 3 Related Work -- 4 Method -- 4.1 Syntactic Graph -- 4.2 Syntactic Graph Prediction Task -- 5 Experiment -- 5.1 Datasets and Baseline Models -- 5.2 Setup and Evaluation Metric. 5.3 Experiment Results -- 6 Analysis -- 6.1 Why Use Parallel Sentence Pairs to Train Syntax Task? -- 6.2 Why the Syntactic Graph Prediction Task Works? -- 7 Conclusions -- References -- Profile Consistency Discrimination -- 1 Introduction -- 2 Relate Work -- 2.1 Natural Language Inference -- 2.2 Role Consistency -- 3 Consistency Discrimination -- 3.1 Problem Definition -- 3.2 Consistency Discriminator -- 4 Experiments Setup -- 4.1 Implementation Details and Evaluations -- 4.2 Baselines -- 5 Result -- 6 Case Study -- 7 Conclusion and Future Work -- References -- BDMS -- H-V: An Improved Coding Layout Based on Erasure Coded Storage System -- 1 Introduction -- 2 Related Work -- 3 HRS(n,k) - VRS(n',k') Encoding Method -- 4 Effect Analysis of HRS(n,k) - VRS(n',k') -- 4.1 Data Transmission Performance Analysis -- 4.2 Storage Redundancy Analysis -- 5 Conclusion -- References -- Astral: An Autoencoder-Based Model for Pedestrian Trajectory Prediction of Variable-Length -- 1 Introduction -- 2 Problem Definitions -- 3 Methodology -- 3.1 Model Framework -- 3.2 Autoencoder -- 3.3 Multi-head Attention -- 3.4 Online Model -- 4 Experiments -- 4.1 Experimental Settings -- 4.2 Evaluation of Trajectory Prediction -- 4.3 Ablation Studies -- 4.4 Case Study -- 5 Related Work -- 5.1 Crowd Interaction -- 5.2 LSTM for Sequence Prediction -- 6 Conclusion -- References -- A Survey on Spatiotemporal Data Processing Techniques in Smart Urban Rail -- 1 Introduction -- 2 Spatiotemporal Data Processing Technology -- 3 Applications of Smart Urban Rail -- 3.1 Intelligent Scheduling -- 3.2 Intelligent Operation Platform -- 3.3 Intelligent Perception -- 3.4 Intelligent Train Control -- 4 Future Work -- 5 Conclusion -- References -- Fast Vehicle Track Counting in Traffic Video -- 1 Introduction -- 2 Related Work -- 3 Preliminary and Problem Statement. 4 An Efficient Vehicle Query Counting Method -- 4.1 Adaptively Choosing Frames for Vehicle Detection -- 4.2 Vehicle Tracking Based on Location and Simple Appearance Features -- 4.3 Cascade Track Judgment and Counting -- 5 Experiments -- 5.1 Settings -- 5.2 Metrics -- 5.3 Experimental Results -- 5.4 Ablation Experiments -- 6 Conclusion -- References -- TSummary: A Traffic Summarization System Using Semantic Words -- 1 Introduction -- 2 System Overview -- 2.1 Feature Extraction -- 2.2 Preliminary Concepts -- 2.3 Structure of TSummary -- 3 Traffic Summarization -- 3.1 Periodic Feature Detection -- 3.2 Road Partitioning -- 3.3 Temporal Merge -- 4 Experiment -- 4.1 Experiment Setup -- 4.2 Evaluation Approach -- 4.3 Performance Evaluation -- 5 Related Work -- 6 Conclusions -- References -- Attention-Cooperated Reinforcement Learning for Multi-agent Path Planning -- 1 Introduction -- 2 Related Work -- 2.1 Classical Path Planning Methods -- 2.2 Learning Based Methods -- 3 Problem Formulation -- 4 Approach -- 4.1 State's Structure -- 4.2 Action Space -- 4.3 Reward Design -- 4.4 Model Architecture -- 5 Experiments -- 5.1 Experiment Setting -- 5.2 Training Details -- 5.3 Metrics -- 5.4 Baselines -- 5.5 Results -- 6 Conclusion -- References -- Big Data-Driven Stable Task Allocation in Ride-Hailing Services -- 1 Introduction -- 2 Related Work -- 3 Problem Definition -- 3.1 Preliminaries and Definition -- 3.2 A Baseline Approach -- 4 Equilibrium Stable Matching and Global Distance Optimization -- 4.1 Chain Algorithm -- 4.2 The Benefit Function for Equilibrium -- 5 Experimental Study -- 6 Conclusion -- References -- Weighted Mean-Field Multi-Agent Reinforcement Learning via Reward Attribution Decomposition -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 3.1 Markov Decision Process and Markov Game -- 3.2 Mean-Field Reinforcement Learning -- 4 Algorithm. 4.1 Weighted Mean-Field Approximation. |
| Record Nr. | UNISA-996483162603316 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Database Systems for Advanced Applications [[electronic resource] ] : 27th International Conference, DASFAA 2022, Virtual Event, April 11–14, 2022, Proceedings, Part II / / edited by Arnab Bhattacharya, Janice Lee Mong Li, Divyakant Agrawal, P. Krishna Reddy, Mukesh Mohania, Anirban Mondal, Vikram Goyal, Rage Uday Kiran
| Database Systems for Advanced Applications [[electronic resource] ] : 27th International Conference, DASFAA 2022, Virtual Event, April 11–14, 2022, Proceedings, Part II / / edited by Arnab Bhattacharya, Janice Lee Mong Li, Divyakant Agrawal, P. Krishna Reddy, Mukesh Mohania, Anirban Mondal, Vikram Goyal, Rage Uday Kiran |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (744 pages) |
| Disciplina | 006.312 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Data mining
Database management Education—Data processing Social sciences—Data processing Machine learning Data Mining and Knowledge Discovery Database Management Computers and Education Computer Application in Social and Behavioral Sciences Machine Learning |
| ISBN | 3-031-00126-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996472069503316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Database Systems for Advanced Applications [[electronic resource] ] : 27th International Conference, DASFAA 2022, Virtual Event, April 11–14, 2022, Proceedings, Part III / / edited by Arnab Bhattacharya, Janice Lee Mong Li, Divyakant Agrawal, P. Krishna Reddy, Mukesh Mohania, Anirban Mondal, Vikram Goyal, Rage Uday Kiran
| Database Systems for Advanced Applications [[electronic resource] ] : 27th International Conference, DASFAA 2022, Virtual Event, April 11–14, 2022, Proceedings, Part III / / edited by Arnab Bhattacharya, Janice Lee Mong Li, Divyakant Agrawal, P. Krishna Reddy, Mukesh Mohania, Anirban Mondal, Vikram Goyal, Rage Uday Kiran |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (577 pages) |
| Disciplina | 005.7565 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Data mining
Database management Computer networks Social sciences—Data processing Application software Artificial intelligence Data Mining and Knowledge Discovery Database Management Computer Communication Networks Computer Application in Social and Behavioral Sciences Computer and Information Systems Applications Artificial Intelligence Gestió de bases de dades |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN | 3-031-00129-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996472069803316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
