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Advances in databases and information systems : 26th European conference, ADBIS 2022, Turin, Italy, September 5-8, 2022, proceedings / / Silvia Chiusano, Tania Cerquitelli, Robert Wrembel (editors)
Advances in databases and information systems : 26th European conference, ADBIS 2022, Turin, Italy, September 5-8, 2022, proceedings / / Silvia Chiusano, Tania Cerquitelli, Robert Wrembel (editors)
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2022]
Descrizione fisica 1 online resource (419 pages)
Disciplina 005.74
Collana Lecture notes in computer science
Soggetto topico Database management
Information technology
ISBN 3-031-15740-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Abstracts of the Keynote Talks -- Toward AI-Powered Data-Driven Education -- Insider Stories: Analyzing Stress, Depression, and Staff Welfare at Major US Companies from Online Reviews -- Tensor Query Processing: Neural Network to speed up Databases and Classical ML! -- Understanding and Rewiring Cities and Societies: A Computational Social Science Perspective -- Contents -- Keynote Talk and Tutorials -- Understanding and Rewiring Cities -- 1 Introduction -- 2 Neighborhoods' Characteristics and Urban Vitality -- 3 How Safety Perception Influences Vitality -- 4 The Interplay of Neighborhoods' Socio-Economic Conditions, Urban Environment, People Behaviors, and Crime -- 5 The Impact of COVID-19 Pandemic on Human Behavior -- 6 Looking Ahead -- References -- AI Approaches in Processing and Using Data in Personalized Medicine -- 1 Introduction -- 2 Different Sources of Patients' Medical Big Data - Collection and Processing -- 3 Emergent Artificial Intelligence Approaches for Supporting Quality Medical Decisions -- 4 Medical Decision Support Systems -- 4.1 Smart Ambient Intelligent Living Environments -- 4.2 Intelligent System for Supporting Cancer Patients -- 5 Conclusion -- References -- Explainable, Interpretable, Trustworthy, Responsible, Ethical, Fair, Verifiable AI... What's Next? -- 1 Introduction -- 2 Explainability -- 3 Interpretability -- 4 The Problem of Bias -- 5 Fairness -- 6 Verification -- 7 Accountability -- 8 Conclusions -- References -- OLAP and NoSQL: Happily Ever After -- 1 Introduction and Motivation -- 2 Schema-on-Read Approaches -- 2.1 Graph OLAP -- 2.2 Approximate OLAP -- 3 Schema-on-Write Approaches -- 3.1 Mono-Model Approaches -- 3.2 Multi-model Approaches -- 4 Conclusion -- References -- What's New in Temporal Databases? -- 1 Introduction -- 2 Query Processing of Primitive Operators.
2.1 Temporal Selection -- 2.2 Temporal Joins -- 3 New Directions in Models and Semantics -- 4 Systems -- 5 Conclusion and Future Directions -- References -- Graph Processing -- An Algebra for Path Manipulation in Graph Databases -- 1 Introduction -- 2 Related Work -- 3 Data Model -- 4 Path Algebra -- 4.1 Operations over Paths -- 4.2 Operations over Sets of Paths -- 4.3 Examples of Queries -- 5 Properties -- 6 Use Cases -- 6.1 Transportation -- 6.2 Proteins -- 7 Discussion -- 7.1 Labels and Repeated Results -- 7.2 Notions of Compatibility -- 7.3 Paths Queries Across Multiple Graphs -- References -- Road Network Graph Representation for Traffic Analysis and Routing -- 1 Introduction -- 2 Related Work -- 3 Road Network Graph Modelling -- 3.1 Primal Graph -- 3.2 Dual Graph -- 4 Generation of Traffic Data -- 5 Traffic Data Integration -- 6 Routing -- 6.1 Managing Road Closures -- 7 Road Network Analysis -- 8 Conclusion -- References -- Parallel Discovery of Top-k Weighted Motifs in Large Graphs -- 1 Introduction -- 2 Related Research -- 3 Background -- 4 The Proposed Approach -- 4.1 Correctness -- 4.2 Extension to 4-Cliques -- 5 Performance Evaluation -- 6 Conclusions -- References -- A Data Quality Framework for Graph-Based Virtual Data Integration Systems -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 3.1 Running Example -- 3.2 Formal Background -- 4 Managing Data Quality in Virtual Data Integration -- 4.1 DC Generation and Graph-Based Representation -- 4.2 Global DC Management -- 5 Global Query Rewriting with Global DCs -- 5.1 Query with DCs -- 6 Validation -- 7 Conclusions and Future Work -- References -- Time Series and Data Streams -- Generating Comparative Explanations of Financial Time Series -- 1 Introduction -- 2 Literature Review -- 3 Data Overview -- 4 Financial Data Summarizer -- 5 Experiments -- 5.1 Intrinsic Evaluation.
5.2 Extrinsic Summary Validation -- 6 Conclusions and Future Works -- References -- Summarizing Edge-Device Data via Core Items -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 3.1 Apache Storm -- 3.2 Stream Summarization -- 4 Algorithms for Core Item Sets Computation -- 4.1 SoftSieving -- 5 Experimental Evaluation -- 6 Conclusion -- References -- Parallel Techniques for Variable Size Segmentation of Time Series Datasets -- 1 Introduction -- 2 Problem Definition and Background -- 2.1 SAX Representation -- 2.2 Similarity Queries -- 2.3 Problem Statement -- 3 Adaptive SAX Based on the Representation's Sum of Squared Errors (ASAX_SSE) -- 3.1 Sum of Squared Errors (SSE) -- 3.2 SSE of PAA Representation Considering One Segment (LSSE) -- 3.3 SSE of PAA Representation Considering All Segments (GSSE) -- 3.4 Variable-Size Segmentation Based on SSE Measurement -- 3.5 Lower Bounding of the Similarity Measure -- 4 Parallel Versions of ASAX_SSE -- 4.1 Parallelization on Data -- 4.2 Parallelization on Segments -- 5 Experiments -- 5.1 Setup -- 5.2 Precision of k-Nearest Neighbor Search -- 5.3 Scalability -- 6 Related Work -- 7 Conclusion -- References -- On Line Analytical Processing -- ORTree: Tuning Diversified Similarity Queries by Means of Data Partitioning -- 1 Introduction -- 2 Background -- 2.1 Range-Tree -- 2.2 MAM - Omni-Technique -- 2.3 The Diversity Problem -- 2.4 Diversity Algorithms -- 2.5 Candidate Selection -- 3 Methodology -- 4 Experiments -- 4.1 Index Creation Time -- 4.2 Quality Experiments -- 4.3 Number of Elements Retrieved -- 4.4 Query Time Evaluation -- 5 Conclusions and Future Work -- References -- A Knowledge-Based Approach to Support Analytic Query Answering in Semantic Data Lakes*-12pt -- 1 Introduction -- 2 Case Study: Azure COVID-19 Data Lake -- 3 Semantic Data Lake: Data Model -- 3.1 Metadata Layer -- 3.2 Knowledge Layer.
4 Integration and Mapping Discovery -- 5 Query Answering -- 6 Evaluation -- 7 Conclusion -- References -- Insight-Based Vocalization of OLAP Sessions -- 1 Introduction -- 2 Related Work -- 3 Overview -- 4 Formal Background -- 5 The Vocalization Process -- 5.1 Insight Generation -- 5.2 Insight Selection -- 5.3 Vocalization -- 6 A Closer Look at the VOOL Modules -- 7 Evaluation and Conclusion -- References -- Advanced Querying -- Querying Temporal Anomalies in Healthcare Information Systems and Beyond -- 1 Introduction -- 2 Related Work -- 3 Temporal Anomalies -- 3.1 Preliminaries -- 3.2 Definition of Temporal Anomalies -- 3.3 Anomaly Labelling and Retrieval -- 4 SQL Implementations -- 4.1 Unfold/Fold -- 4.2 Unfold/Fold Join Filtered -- 4.3 Window Function -- 5 Experimental Evaluation -- 5.1 Setup and Dataset -- 5.2 Results -- 6 Conclusion and Future Work -- References -- Soft Spatial Querying on JSON Data Sets -- 1 Introduction -- 2 Background -- 2.1 Brief Introduction to Fuzzy Sets -- 2.2 Related Work -- 2.3 The J-CO Framework -- 3 Case Study and J-CO-QL+ Script -- 3.1 Case Study -- 3.2 Definition of Fuzzy Concepts -- 3.3 Processing a GeoJSON Document -- 3.4 Soft Spatial Querying -- 4 Conclusions -- References -- Maximum Range-Sum for Dynamically Occurring Objects with Decaying Weights -- 1 Introduction -- 2 Preliminaries -- 3 Approximate Solution to DDW-MaxRS -- 3.1 Properties of the Approximate Solution -- 3.2 Memory-Efficient Approximate Solution -- 4 Generalization -- 5 Experimental Study -- 6 Related Work -- 7 Conclusions and Future Work -- References -- Performance -- Storage Management with Multi-Version Partitioned BTrees -- 1 Introduction -- 2 Architecture of Multi-Version Partitioned BTrees -- 3 Cached Partition: Stop Re-writing Valid Data -- 4 Garbage Collection and Space Reclamation -- 5 Experimental Evaluation -- 6 Conclusion.
References -- Generalization Aware Compression of Molecular Trajectories -- 1 Introduction -- 2 Background -- 3 Methodology -- 4 Experiments -- 5 Conclusions and Future Work -- References -- Analysing Workload Trends for Boosting Triple Stores Performance -- 1 Introduction -- 2 Background and Related Work -- 2.1 RDF Graph and Queries Processing -- 2.2 Indexing and Cache -- 2.3 Replication -- 2.4 Workload Adaption -- 2.5 Heat Query -- 3 Heat Item Gets Colder -- 3.1 Smoothing Methods -- 3.2 Exponential Smoothing -- 3.3 Holt-Winters' Additive Method -- 4 Experimental Evaluation -- 4.1 Exponential Smoothing -- 4.2 Hot Data Parts -- 4.3 Seasonality Factors and Capacity -- 5 Conclusion and Future Work -- References -- Machine Learning -- Comparison of Models Built Using AutoML and Data Fusion -- 1 Introduction -- 2 Related Work -- 3 Problem Statement -- 4 Proposed Approach -- 4.1 Datasets Description -- 4.2 Data Fusion Process -- 4.3 Experimental Design -- 4.4 Performance Evaluation -- 5 Conclusion and Future Work -- References -- Dimensional Data KNN-Based Imputation -- 1 Introduction -- 2 Related Work -- 3 DW Dimension -- 4 Distance Between Dimension Instances -- 4.1 Attribute Distance -- 4.2 Hierarchy Level Instance Distance -- 4.3 Hierarchy Instance Distance -- 4.4 Dimension Instance Weight -- 5 H-OLAPKNN Imputation -- 5.1 H-OLAPKNN Overview -- 5.2 Imputation for Parameters by OLAPKNN -- 6 Experimental Assessment -- 6.1 Technical Environment and Datasets -- 6.2 Experimental Methodology -- 6.3 Results and Analysis -- 7 Conclusion and Future Work -- References -- Feature Ranking from Random Forest Through Complex Network's Centrality Measures*2mm -- 1 Introduction -- 2 Related Work -- 2.1 Feature Selection and Ranking -- 2.2 Random Forests -- 2.3 Complex Networks -- 3 From Trees in a Random Forest to a Complex Network -- 4 Experimental Setup.
5 Results and Discussion.
Record Nr. UNINA-9910590049403321
Cham, Switzerland : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advances in databases and information systems : 26th European conference, ADBIS 2022, Turin, Italy, September 5-8, 2022, proceedings / / Silvia Chiusano, Tania Cerquitelli, Robert Wrembel (editors)
Advances in databases and information systems : 26th European conference, ADBIS 2022, Turin, Italy, September 5-8, 2022, proceedings / / Silvia Chiusano, Tania Cerquitelli, Robert Wrembel (editors)
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2022]
Descrizione fisica 1 online resource (419 pages)
Disciplina 005.74
Collana Lecture notes in computer science
Soggetto topico Database management
Information technology
ISBN 3-031-15740-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Abstracts of the Keynote Talks -- Toward AI-Powered Data-Driven Education -- Insider Stories: Analyzing Stress, Depression, and Staff Welfare at Major US Companies from Online Reviews -- Tensor Query Processing: Neural Network to speed up Databases and Classical ML! -- Understanding and Rewiring Cities and Societies: A Computational Social Science Perspective -- Contents -- Keynote Talk and Tutorials -- Understanding and Rewiring Cities -- 1 Introduction -- 2 Neighborhoods' Characteristics and Urban Vitality -- 3 How Safety Perception Influences Vitality -- 4 The Interplay of Neighborhoods' Socio-Economic Conditions, Urban Environment, People Behaviors, and Crime -- 5 The Impact of COVID-19 Pandemic on Human Behavior -- 6 Looking Ahead -- References -- AI Approaches in Processing and Using Data in Personalized Medicine -- 1 Introduction -- 2 Different Sources of Patients' Medical Big Data - Collection and Processing -- 3 Emergent Artificial Intelligence Approaches for Supporting Quality Medical Decisions -- 4 Medical Decision Support Systems -- 4.1 Smart Ambient Intelligent Living Environments -- 4.2 Intelligent System for Supporting Cancer Patients -- 5 Conclusion -- References -- Explainable, Interpretable, Trustworthy, Responsible, Ethical, Fair, Verifiable AI... What's Next? -- 1 Introduction -- 2 Explainability -- 3 Interpretability -- 4 The Problem of Bias -- 5 Fairness -- 6 Verification -- 7 Accountability -- 8 Conclusions -- References -- OLAP and NoSQL: Happily Ever After -- 1 Introduction and Motivation -- 2 Schema-on-Read Approaches -- 2.1 Graph OLAP -- 2.2 Approximate OLAP -- 3 Schema-on-Write Approaches -- 3.1 Mono-Model Approaches -- 3.2 Multi-model Approaches -- 4 Conclusion -- References -- What's New in Temporal Databases? -- 1 Introduction -- 2 Query Processing of Primitive Operators.
2.1 Temporal Selection -- 2.2 Temporal Joins -- 3 New Directions in Models and Semantics -- 4 Systems -- 5 Conclusion and Future Directions -- References -- Graph Processing -- An Algebra for Path Manipulation in Graph Databases -- 1 Introduction -- 2 Related Work -- 3 Data Model -- 4 Path Algebra -- 4.1 Operations over Paths -- 4.2 Operations over Sets of Paths -- 4.3 Examples of Queries -- 5 Properties -- 6 Use Cases -- 6.1 Transportation -- 6.2 Proteins -- 7 Discussion -- 7.1 Labels and Repeated Results -- 7.2 Notions of Compatibility -- 7.3 Paths Queries Across Multiple Graphs -- References -- Road Network Graph Representation for Traffic Analysis and Routing -- 1 Introduction -- 2 Related Work -- 3 Road Network Graph Modelling -- 3.1 Primal Graph -- 3.2 Dual Graph -- 4 Generation of Traffic Data -- 5 Traffic Data Integration -- 6 Routing -- 6.1 Managing Road Closures -- 7 Road Network Analysis -- 8 Conclusion -- References -- Parallel Discovery of Top-k Weighted Motifs in Large Graphs -- 1 Introduction -- 2 Related Research -- 3 Background -- 4 The Proposed Approach -- 4.1 Correctness -- 4.2 Extension to 4-Cliques -- 5 Performance Evaluation -- 6 Conclusions -- References -- A Data Quality Framework for Graph-Based Virtual Data Integration Systems -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 3.1 Running Example -- 3.2 Formal Background -- 4 Managing Data Quality in Virtual Data Integration -- 4.1 DC Generation and Graph-Based Representation -- 4.2 Global DC Management -- 5 Global Query Rewriting with Global DCs -- 5.1 Query with DCs -- 6 Validation -- 7 Conclusions and Future Work -- References -- Time Series and Data Streams -- Generating Comparative Explanations of Financial Time Series -- 1 Introduction -- 2 Literature Review -- 3 Data Overview -- 4 Financial Data Summarizer -- 5 Experiments -- 5.1 Intrinsic Evaluation.
5.2 Extrinsic Summary Validation -- 6 Conclusions and Future Works -- References -- Summarizing Edge-Device Data via Core Items -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 3.1 Apache Storm -- 3.2 Stream Summarization -- 4 Algorithms for Core Item Sets Computation -- 4.1 SoftSieving -- 5 Experimental Evaluation -- 6 Conclusion -- References -- Parallel Techniques for Variable Size Segmentation of Time Series Datasets -- 1 Introduction -- 2 Problem Definition and Background -- 2.1 SAX Representation -- 2.2 Similarity Queries -- 2.3 Problem Statement -- 3 Adaptive SAX Based on the Representation's Sum of Squared Errors (ASAX_SSE) -- 3.1 Sum of Squared Errors (SSE) -- 3.2 SSE of PAA Representation Considering One Segment (LSSE) -- 3.3 SSE of PAA Representation Considering All Segments (GSSE) -- 3.4 Variable-Size Segmentation Based on SSE Measurement -- 3.5 Lower Bounding of the Similarity Measure -- 4 Parallel Versions of ASAX_SSE -- 4.1 Parallelization on Data -- 4.2 Parallelization on Segments -- 5 Experiments -- 5.1 Setup -- 5.2 Precision of k-Nearest Neighbor Search -- 5.3 Scalability -- 6 Related Work -- 7 Conclusion -- References -- On Line Analytical Processing -- ORTree: Tuning Diversified Similarity Queries by Means of Data Partitioning -- 1 Introduction -- 2 Background -- 2.1 Range-Tree -- 2.2 MAM - Omni-Technique -- 2.3 The Diversity Problem -- 2.4 Diversity Algorithms -- 2.5 Candidate Selection -- 3 Methodology -- 4 Experiments -- 4.1 Index Creation Time -- 4.2 Quality Experiments -- 4.3 Number of Elements Retrieved -- 4.4 Query Time Evaluation -- 5 Conclusions and Future Work -- References -- A Knowledge-Based Approach to Support Analytic Query Answering in Semantic Data Lakes*-12pt -- 1 Introduction -- 2 Case Study: Azure COVID-19 Data Lake -- 3 Semantic Data Lake: Data Model -- 3.1 Metadata Layer -- 3.2 Knowledge Layer.
4 Integration and Mapping Discovery -- 5 Query Answering -- 6 Evaluation -- 7 Conclusion -- References -- Insight-Based Vocalization of OLAP Sessions -- 1 Introduction -- 2 Related Work -- 3 Overview -- 4 Formal Background -- 5 The Vocalization Process -- 5.1 Insight Generation -- 5.2 Insight Selection -- 5.3 Vocalization -- 6 A Closer Look at the VOOL Modules -- 7 Evaluation and Conclusion -- References -- Advanced Querying -- Querying Temporal Anomalies in Healthcare Information Systems and Beyond -- 1 Introduction -- 2 Related Work -- 3 Temporal Anomalies -- 3.1 Preliminaries -- 3.2 Definition of Temporal Anomalies -- 3.3 Anomaly Labelling and Retrieval -- 4 SQL Implementations -- 4.1 Unfold/Fold -- 4.2 Unfold/Fold Join Filtered -- 4.3 Window Function -- 5 Experimental Evaluation -- 5.1 Setup and Dataset -- 5.2 Results -- 6 Conclusion and Future Work -- References -- Soft Spatial Querying on JSON Data Sets -- 1 Introduction -- 2 Background -- 2.1 Brief Introduction to Fuzzy Sets -- 2.2 Related Work -- 2.3 The J-CO Framework -- 3 Case Study and J-CO-QL+ Script -- 3.1 Case Study -- 3.2 Definition of Fuzzy Concepts -- 3.3 Processing a GeoJSON Document -- 3.4 Soft Spatial Querying -- 4 Conclusions -- References -- Maximum Range-Sum for Dynamically Occurring Objects with Decaying Weights -- 1 Introduction -- 2 Preliminaries -- 3 Approximate Solution to DDW-MaxRS -- 3.1 Properties of the Approximate Solution -- 3.2 Memory-Efficient Approximate Solution -- 4 Generalization -- 5 Experimental Study -- 6 Related Work -- 7 Conclusions and Future Work -- References -- Performance -- Storage Management with Multi-Version Partitioned BTrees -- 1 Introduction -- 2 Architecture of Multi-Version Partitioned BTrees -- 3 Cached Partition: Stop Re-writing Valid Data -- 4 Garbage Collection and Space Reclamation -- 5 Experimental Evaluation -- 6 Conclusion.
References -- Generalization Aware Compression of Molecular Trajectories -- 1 Introduction -- 2 Background -- 3 Methodology -- 4 Experiments -- 5 Conclusions and Future Work -- References -- Analysing Workload Trends for Boosting Triple Stores Performance -- 1 Introduction -- 2 Background and Related Work -- 2.1 RDF Graph and Queries Processing -- 2.2 Indexing and Cache -- 2.3 Replication -- 2.4 Workload Adaption -- 2.5 Heat Query -- 3 Heat Item Gets Colder -- 3.1 Smoothing Methods -- 3.2 Exponential Smoothing -- 3.3 Holt-Winters' Additive Method -- 4 Experimental Evaluation -- 4.1 Exponential Smoothing -- 4.2 Hot Data Parts -- 4.3 Seasonality Factors and Capacity -- 5 Conclusion and Future Work -- References -- Machine Learning -- Comparison of Models Built Using AutoML and Data Fusion -- 1 Introduction -- 2 Related Work -- 3 Problem Statement -- 4 Proposed Approach -- 4.1 Datasets Description -- 4.2 Data Fusion Process -- 4.3 Experimental Design -- 4.4 Performance Evaluation -- 5 Conclusion and Future Work -- References -- Dimensional Data KNN-Based Imputation -- 1 Introduction -- 2 Related Work -- 3 DW Dimension -- 4 Distance Between Dimension Instances -- 4.1 Attribute Distance -- 4.2 Hierarchy Level Instance Distance -- 4.3 Hierarchy Instance Distance -- 4.4 Dimension Instance Weight -- 5 H-OLAPKNN Imputation -- 5.1 H-OLAPKNN Overview -- 5.2 Imputation for Parameters by OLAPKNN -- 6 Experimental Assessment -- 6.1 Technical Environment and Datasets -- 6.2 Experimental Methodology -- 6.3 Results and Analysis -- 7 Conclusion and Future Work -- References -- Feature Ranking from Random Forest Through Complex Network's Centrality Measures*2mm -- 1 Introduction -- 2 Related Work -- 2.1 Feature Selection and Ranking -- 2.2 Random Forests -- 2.3 Complex Networks -- 3 From Trees in a Random Forest to a Complex Network -- 4 Experimental Setup.
5 Results and Discussion.
Record Nr. UNISA-996485665503316
Cham, Switzerland : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
New Trends in Databases and Information Systems [[electronic resource] ] : ADBIS 2018 Short Papers and Workshops, AIQA, BIGPMED, CSACDB, M2U, BigDataMAPS, ISTREND, DC, Budapest, Hungary, September, 2-5, 2018, Proceedings / / edited by András Benczúr, Bernhard Thalheim, Tomáš Horváth, Silvia Chiusano, Tania Cerquitelli, Csaba Sidló, Peter Z. Revesz
New Trends in Databases and Information Systems [[electronic resource] ] : ADBIS 2018 Short Papers and Workshops, AIQA, BIGPMED, CSACDB, M2U, BigDataMAPS, ISTREND, DC, Budapest, Hungary, September, 2-5, 2018, Proceedings / / edited by András Benczúr, Bernhard Thalheim, Tomáš Horváth, Silvia Chiusano, Tania Cerquitelli, Csaba Sidló, Peter Z. Revesz
Edizione [1st ed. 2018.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018
Descrizione fisica 1 online resource (XXIV, 424 p. 111 illus.)
Disciplina 005.74
Collana Communications in Computer and Information Science
Soggetto topico Database management
Computers
Database Management
Information Systems and Communication Service
ISBN 3-030-00063-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto ADBIS 2018 Short Papers -- First Workshop on Advances on Big Data Management, Analytics, Data Privacy and Security, BigDataMAPS 2018 -- First International Workshop on New Frontiers on Meta-data Management and Usage, M2U 2018 -- Citizen Science Applications and Citizen Databases Workshop, CSADB 2018 -- International Workshop on Articial Intelligence for Question Answering, AI*QA 2018 -- International Workshop on BIG Data Storage, Processing and Mining for Personalized MEDicine, BIGPMED 2018 -- Current Trends in Contemporary Information Systems and Their Architectures, ISTREND 2018 -- Doctoral Consortium.
Record Nr. UNINA-9910299290303321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
New Trends in Databases and Information Systems [[electronic resource] ] : ADBIS 2016 Short Papers and Workshops, BigDap, DCSA, DC, Prague, Czech Republic, August 28-31, 2016, Proceedings / / edited by Mirjana Ivanović, Bernhard Thalheim, Barbara Catania, Klaus-Dieter Schewe, Mārīte Kirikova, Petr Šaloun, Ajantha Dahanayake, Tania Cerquitelli, Elena Baralis, Pietro Michiardi
New Trends in Databases and Information Systems [[electronic resource] ] : ADBIS 2016 Short Papers and Workshops, BigDap, DCSA, DC, Prague, Czech Republic, August 28-31, 2016, Proceedings / / edited by Mirjana Ivanović, Bernhard Thalheim, Barbara Catania, Klaus-Dieter Schewe, Mārīte Kirikova, Petr Šaloun, Ajantha Dahanayake, Tania Cerquitelli, Elena Baralis, Pietro Michiardi
Edizione [1st ed. 2016.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Descrizione fisica 1 online resource (XIV, 235 p. 78 illus.)
Disciplina 005.74
Collana Communications in Computer and Information Science
Soggetto topico Database management
Application software
Information storage and retrieval
Data mining
Database Management
Information Systems Applications (incl. Internet)
Information Storage and Retrieval
Data Mining and Knowledge Discovery
ISBN 3-319-44066-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto ADBIS Short Papers -- Third International Workshop on Big Data Applications and Principles, BigDap 2016 -- Second International Workshop on Data Centered Smart Applications, DCSA 2016 -- ADBIS Doctoral Consortium.
Record Nr. UNINA-9910255008703321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Predictive maintenance in smart factories : architectures, methodologies, and use-cases / / Tania Cerquitelli [and five others], editors
Predictive maintenance in smart factories : architectures, methodologies, and use-cases / / Tania Cerquitelli [and five others], editors
Pubbl/distr/stampa Singapore : , : Springer, , [2021]
Descrizione fisica 1 online resource (239 pages)
Disciplina 629.8
Collana Information fusion and data science
Soggetto topico Predictive control
ISBN 981-16-2940-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Contents -- Contributors -- Acronyms -- Methodologies and Enabling Technologies -- Industrial Digitisation and Maintenance: Present and Future -- 1 Introduction -- 2 Literature Review -- 2.1 Maintenance Approaches -- 2.2 Data Management Architectures -- 2.3 Data-Driven Analytics: Methodologies and Algorithms -- 2.4 Integrated Solutions -- 3 Key Challenges Identified -- 4 Outlook -- 4.1 The SERENA Vision -- References -- A Hybrid Cloud-to-Edge Predictive Maintenance Platform -- 1 Introduction -- 2 Related Works -- 2.1 Predictive Maintenance in Industry 4.0 -- 2.2 Cloud and Edge Computing -- 2.3 Predictive Maintenance Technologies -- 3 SERENA Design -- 3.1 Intermodal Collaboration -- 3.2 Data Management -- 3.3 Service Orchestration -- 3.4 Security -- 4 SERENA Architecture -- 4.1 Core Services -- 4.2 Peripheral Services -- 4.3 Provisioning and Deployment -- 5 Conclusions -- References -- Data-Driven Predictive Maintenance: A Methodology Primer -- 1 Introduction -- 2 Predictive Maintenance: Main Concepts and Key Standards -- 2.1 The European Standard CEN-EN 13306 -- 2.2 Guidelines and Requirements for Automated Maintenance Software -- 2.3 Guidelines for Automated Condition Monitoring System and Diagnostics -- 2.4 Guidelines for Prognosis -- 3 Data-Driven Methodologies -- 3.1 Data-Driven Modelling and Physics-Based Modelling -- 3.2 Predictive and Descriptive Data Analytics -- 3.3 Model Building, Deployment, and Updating -- 3.4 RUL Estimation: Key Concepts -- 4 The SERENA Data-Driven Pipeline -- 4.1 Data Preparation -- 4.2 Semi-supervised Data Labelling -- 4.3 Predictive Analytics -- 4.4 Self Assessment of Model Drift -- 4.5 RUL Estimation -- 5 Data Formats and Models -- 5.1 A Linked Data Approach -- 5.2 MIMOSA -- 6 Data Analytics Architecture -- 6.1 Technologies and Tools for Analytics Services -- 6.2 Edge Analytics Applications.
7 Discussion and Future Research Directions -- References -- Services to Facilitate Predictive Maintenance in Industry4.0 -- 1 Introduction -- 2 Literature Review -- 3 Predictive Maintenance Services in SERENA -- 3.1 Physics-Based and Hybrid Modelling (O& -- M Analytics Toolbox) -- 3.2 Data-Driven Analytics -- 3.3 Maintenance Aware Scheduling -- 3.4 Operator Support Services -- 4 Conclusion -- References -- Industrial Use-cases -- Predictive Analytics in Robotic Industry -- 1 Introduction -- 2 SERENA Contribution -- 2.1 Architecture -- 2.2 Approach -- 2.3 Results -- 2.4 System Deployment -- 3 Discussion -- 4 Outlook -- References -- Remote Condition Monitoring and Control for Maintenance Activities in Coordinate Measurement Machine: A Data-Driven Approach for the Metrology Engineering Industry -- 1 TRIMEK Use Case -- 1.1 Introduction -- 1.2 Coordinate Measuring Machine (CMM) -- 1.3 CMM Subsystem Under Study -- 1.4 Main Objective of the Test Bed -- 1.5 Needs and Motivation -- 1.6 Expected Contribution of SERENA -- 2 SERENA System in TRIMEK Use Case -- 2.1 Remote Factory Condition and Control -- 2.2 AI Condition-Based Maintenance and Planning Techniques -- 2.3 AR-Based Technologies for Remote Assistance and Human Operator Support -- 2.4 Cloud-Based Platform for Versatile Remote Diagnostics -- 3 Results -- 4 Conclusion -- References -- Estimating Remaining Useful Life: A Data-Driven Methodology for the White Goods Industry -- 1 Introduction -- 2 The White Goods Industry: Use Case Description -- 2.1 Industrial Process -- 2.2 Preventive Maintenance: Current Status and Requirements -- 3 Literature Review -- 4 The SERENA Data Analytics Pipeline -- 4.1 Data Sources -- 4.2 Preprocessing -- 4.3 Time-Window Degradation Analysis -- 4.4 Model Building and RUL Prediction -- 4.5 Deployment -- 5 Results -- 5.1 Training and Test Dataset.
5.2 Experimental Settings -- 5.3 Model Building and Test -- 6 Lessons Learned -- 7 Conclusions -- References -- Predictive Analytics in the Production of Elevators -- 1 Challenges and Needs in Elevator Production Industry -- 2 Sensors and Data Acquisition Devices for Remote Condition Monitoring -- 2.1 Development of a Low-Cost Solution -- 2.2 Edge Processing -- 2.3 Use Case Results -- 2.4 Summary -- 3 Remote Factory Condition Monitoring and Predictive Analytics -- 3.1 Remote Connection to Production Line -- 3.2 Versatile Cloud-Based Platform for Remote Diagnostics -- 3.3 Predictive AI Condition-Based Maintenance and Service Scheduling -- 3.4 AR-Based Assistance for Operators During Maintenance -- 4 Integrated Solution and Technical Architecture -- 5 Impact -- 6 Conclusion -- References -- Predictive Maintenance in the Production of Steel Bars: A Data-Driven Approach -- 1 Introduction -- 2 Literature Review -- 3 Maintenance Needs and Challenges in the Steel Bar Production Industry -- 4 Steel Bar Production Case Study: Present and Future -- 4.1 Maintenance Needs -- 4.2 Equipment Description -- 4.3 Steel Bar Production Process -- 5 SERENA System in the Steel Bar Production Case -- 5.1 Architecture -- 5.2 Data Connections -- 5.3 Data Acquisition -- 5.4 Data Analytics -- 5.5 Results -- 5.6 System Deployment -- 6 Discussion and Conclusion -- References -- In-Situ Monitoring of Additive Manufacturing -- 1 Introduction -- 2 Additive Manufacturing: Process and Methods -- 3 In-Situ Monitoring: Current Solutions -- 4 Case-Study: Layer-Wise Defects Monitoring System for DMLS Based on Visible-Range Imaging -- 4.1 Data Acquisition and Processing System -- 4.2 Defects Detection Algorithms -- 4.3 Part Profile Monitoring Algorithm -- 4.4 Dataset Augmentation with GAN -- 5 Experimental Results -- 6 Conclusion and Future Works -- References -- Appendix Glossary.
Index.
Record Nr. UNISA-996466730103316
Singapore : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Predictive maintenance in smart factories : architectures, methodologies, and use-cases / / Tania Cerquitelli [and five others], editors
Predictive maintenance in smart factories : architectures, methodologies, and use-cases / / Tania Cerquitelli [and five others], editors
Pubbl/distr/stampa Singapore : , : Springer, , [2021]
Descrizione fisica 1 online resource (239 pages)
Disciplina 629.8
Collana Information fusion and data science
Soggetto topico Predictive control
ISBN 981-16-2940-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Contents -- Contributors -- Acronyms -- Methodologies and Enabling Technologies -- Industrial Digitisation and Maintenance: Present and Future -- 1 Introduction -- 2 Literature Review -- 2.1 Maintenance Approaches -- 2.2 Data Management Architectures -- 2.3 Data-Driven Analytics: Methodologies and Algorithms -- 2.4 Integrated Solutions -- 3 Key Challenges Identified -- 4 Outlook -- 4.1 The SERENA Vision -- References -- A Hybrid Cloud-to-Edge Predictive Maintenance Platform -- 1 Introduction -- 2 Related Works -- 2.1 Predictive Maintenance in Industry 4.0 -- 2.2 Cloud and Edge Computing -- 2.3 Predictive Maintenance Technologies -- 3 SERENA Design -- 3.1 Intermodal Collaboration -- 3.2 Data Management -- 3.3 Service Orchestration -- 3.4 Security -- 4 SERENA Architecture -- 4.1 Core Services -- 4.2 Peripheral Services -- 4.3 Provisioning and Deployment -- 5 Conclusions -- References -- Data-Driven Predictive Maintenance: A Methodology Primer -- 1 Introduction -- 2 Predictive Maintenance: Main Concepts and Key Standards -- 2.1 The European Standard CEN-EN 13306 -- 2.2 Guidelines and Requirements for Automated Maintenance Software -- 2.3 Guidelines for Automated Condition Monitoring System and Diagnostics -- 2.4 Guidelines for Prognosis -- 3 Data-Driven Methodologies -- 3.1 Data-Driven Modelling and Physics-Based Modelling -- 3.2 Predictive and Descriptive Data Analytics -- 3.3 Model Building, Deployment, and Updating -- 3.4 RUL Estimation: Key Concepts -- 4 The SERENA Data-Driven Pipeline -- 4.1 Data Preparation -- 4.2 Semi-supervised Data Labelling -- 4.3 Predictive Analytics -- 4.4 Self Assessment of Model Drift -- 4.5 RUL Estimation -- 5 Data Formats and Models -- 5.1 A Linked Data Approach -- 5.2 MIMOSA -- 6 Data Analytics Architecture -- 6.1 Technologies and Tools for Analytics Services -- 6.2 Edge Analytics Applications.
7 Discussion and Future Research Directions -- References -- Services to Facilitate Predictive Maintenance in Industry4.0 -- 1 Introduction -- 2 Literature Review -- 3 Predictive Maintenance Services in SERENA -- 3.1 Physics-Based and Hybrid Modelling (O& -- M Analytics Toolbox) -- 3.2 Data-Driven Analytics -- 3.3 Maintenance Aware Scheduling -- 3.4 Operator Support Services -- 4 Conclusion -- References -- Industrial Use-cases -- Predictive Analytics in Robotic Industry -- 1 Introduction -- 2 SERENA Contribution -- 2.1 Architecture -- 2.2 Approach -- 2.3 Results -- 2.4 System Deployment -- 3 Discussion -- 4 Outlook -- References -- Remote Condition Monitoring and Control for Maintenance Activities in Coordinate Measurement Machine: A Data-Driven Approach for the Metrology Engineering Industry -- 1 TRIMEK Use Case -- 1.1 Introduction -- 1.2 Coordinate Measuring Machine (CMM) -- 1.3 CMM Subsystem Under Study -- 1.4 Main Objective of the Test Bed -- 1.5 Needs and Motivation -- 1.6 Expected Contribution of SERENA -- 2 SERENA System in TRIMEK Use Case -- 2.1 Remote Factory Condition and Control -- 2.2 AI Condition-Based Maintenance and Planning Techniques -- 2.3 AR-Based Technologies for Remote Assistance and Human Operator Support -- 2.4 Cloud-Based Platform for Versatile Remote Diagnostics -- 3 Results -- 4 Conclusion -- References -- Estimating Remaining Useful Life: A Data-Driven Methodology for the White Goods Industry -- 1 Introduction -- 2 The White Goods Industry: Use Case Description -- 2.1 Industrial Process -- 2.2 Preventive Maintenance: Current Status and Requirements -- 3 Literature Review -- 4 The SERENA Data Analytics Pipeline -- 4.1 Data Sources -- 4.2 Preprocessing -- 4.3 Time-Window Degradation Analysis -- 4.4 Model Building and RUL Prediction -- 4.5 Deployment -- 5 Results -- 5.1 Training and Test Dataset.
5.2 Experimental Settings -- 5.3 Model Building and Test -- 6 Lessons Learned -- 7 Conclusions -- References -- Predictive Analytics in the Production of Elevators -- 1 Challenges and Needs in Elevator Production Industry -- 2 Sensors and Data Acquisition Devices for Remote Condition Monitoring -- 2.1 Development of a Low-Cost Solution -- 2.2 Edge Processing -- 2.3 Use Case Results -- 2.4 Summary -- 3 Remote Factory Condition Monitoring and Predictive Analytics -- 3.1 Remote Connection to Production Line -- 3.2 Versatile Cloud-Based Platform for Remote Diagnostics -- 3.3 Predictive AI Condition-Based Maintenance and Service Scheduling -- 3.4 AR-Based Assistance for Operators During Maintenance -- 4 Integrated Solution and Technical Architecture -- 5 Impact -- 6 Conclusion -- References -- Predictive Maintenance in the Production of Steel Bars: A Data-Driven Approach -- 1 Introduction -- 2 Literature Review -- 3 Maintenance Needs and Challenges in the Steel Bar Production Industry -- 4 Steel Bar Production Case Study: Present and Future -- 4.1 Maintenance Needs -- 4.2 Equipment Description -- 4.3 Steel Bar Production Process -- 5 SERENA System in the Steel Bar Production Case -- 5.1 Architecture -- 5.2 Data Connections -- 5.3 Data Acquisition -- 5.4 Data Analytics -- 5.5 Results -- 5.6 System Deployment -- 6 Discussion and Conclusion -- References -- In-Situ Monitoring of Additive Manufacturing -- 1 Introduction -- 2 Additive Manufacturing: Process and Methods -- 3 In-Situ Monitoring: Current Solutions -- 4 Case-Study: Layer-Wise Defects Monitoring System for DMLS Based on Visible-Range Imaging -- 4.1 Data Acquisition and Processing System -- 4.2 Defects Detection Algorithms -- 4.3 Part Profile Monitoring Algorithm -- 4.4 Dataset Augmentation with GAN -- 5 Experimental Results -- 6 Conclusion and Future Works -- References -- Appendix Glossary.
Index.
Record Nr. UNINA-9910739409303321
Singapore : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Transparent Data Mining for Big and Small Data [[electronic resource] /] / edited by Tania Cerquitelli, Daniele Quercia, Frank Pasquale
Transparent Data Mining for Big and Small Data [[electronic resource] /] / edited by Tania Cerquitelli, Daniele Quercia, Frank Pasquale
Edizione [1st ed. 2017.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Descrizione fisica 1 online resource (XV, 215 p. 23 illus. in color.)
Disciplina 006.312
Collana Studies in Big Data
Soggetto topico Data mining
Mass media
Law
Algorithms
Computational complexity
Computer simulation
Big data
Data Mining and Knowledge Discovery
IT Law, Media Law, Intellectual Property
Algorithm Analysis and Problem Complexity
Complexity
Simulation and Modeling
Big Data/Analytics
ISBN 3-319-54024-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Part I: Transparent Mining -- Chapter 1: The Tyranny of Data? The Bright and Dark Sides of Data-Driven Decision-Making for Social Good -- Chapter 2: Enabling Accountability of Algorithmic Media: Transparency as a Constructive and Critical Lens -- Chapter 3: The Princeton Web Transparency and Accountability Project -- Part II: Algorithmic solutions -- Chapter 4: Algorithmic Transparency via Quantitative Input Influence -- Chapter 5 -- Learning Interpretable Classification Rules with Boolean Compressed Sensing -- Chapter 6: Visualizations of Deep Neural Networks in Computer Vision: A Survey -- Part III: Regulatory solutions -- Chapter 7: Beyond the EULA: Improving Consent for Data Mining -- Chapter 8: Regulating Algorithms Regulation? First Ethico-legal Principles, Problems and Opportunities of Algorithms -- Chapter 9: Algorithm Watch: What Role Can a Watchdog Organization Play in Ensuring Algorithmic Accountability?
Record Nr. UNINA-9910254316603321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui