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Advanced web and network technologies, and applications : PWEB 2008 international workshops, BIDM, IWHDM, and DEWEB, Shenyang, China, April 26-28, 2008 / / edited by Yoshiharu Ishikawa [and six others]
| Advanced web and network technologies, and applications : PWEB 2008 international workshops, BIDM, IWHDM, and DEWEB, Shenyang, China, April 26-28, 2008 / / edited by Yoshiharu Ishikawa [and six others] |
| Edizione | [1st ed. 2008.] |
| Pubbl/distr/stampa | Berlin, Germany : , : Springer, , [2008] |
| Descrizione fisica | 1 online resource (XIV, 247 p. 85 illus.) |
| Disciplina | 004.678 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico |
Data mining
World Wide Web Medical informatics |
| ISBN | 3-540-89376-8 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | The First Workshop on Business Intelligence and Data Mining -- Moving Objects Databases Based on Dynamic Transportation Networks: Modeling, Indexing, and Implementation -- Approach to Detection of Community’s Consensus and Interest -- A Comparative Empirical Study on the Margin Setting of Stock Index Futures Calendar Spread Trading -- A Study on Multi-word Extraction from Chinese Documents -- Extracting Information from Semi-structured Web Documents: A Framework -- Discovering Interesting Classification Rules with Particle Swarm Algorithm -- International Workshop on Health Data Management -- Improving the Use, Analysis and Integration of Patient Health Data -- DM-Based Medical Solution and Application -- Learning-Function-Augmented Inferences of Causalities Implied in Health Data -- Support Vector Machine for Outlier Detection in Breast Cancer Survivability Prediction -- An Empirical Study of Combined Classifiers for Knowledge Discovery on Medical Data Bases -- Tracing the Application of Clinical Guidelines -- Doctoral Consortium on Data Engineering and Web Technology Research -- The Research on the Algorithms of Keyword Search in Relational Database -- An Approach to Monitor Scenario-Based Temporal Properties in Web Service Compositions -- Efficient Authentication and Authorization Infrastructure for Mobile Users -- An Effective Feature Selection Method Using the Contribution Likelihood Ratio of Attributes for Classification -- Unsupervised Text Learning Based on Context Mixture Model with Dirichlet Prior -- The Knowledge Discovery Research on User’s Mobility of Communication Service Provider -- Protecting Information Sharing in Distributed Collaborative Environment -- Relevance Feedback Learning for Web Image Retrieval Using Soft Support Vector Machine -- Feature Matrix Extraction and Classification of XML Pages -- Tuning the Cardinality of Skyline -- An HMM Approach to Anonymity Analysis of Continuous Mixes. |
| Record Nr. | UNINA-9910484327703321 |
| Berlin, Germany : , : Springer, , [2008] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advanced web and network technologies, and applications : PWEB 2008 international workshops, BIDM, IWHDM, and DEWEB, Shenyang, China, April 26-28, 2008 / / edited by Yoshiharu Ishikawa [and six others]
| Advanced web and network technologies, and applications : PWEB 2008 international workshops, BIDM, IWHDM, and DEWEB, Shenyang, China, April 26-28, 2008 / / edited by Yoshiharu Ishikawa [and six others] |
| Edizione | [1st ed. 2008.] |
| Pubbl/distr/stampa | Berlin, Germany : , : Springer, , [2008] |
| Descrizione fisica | 1 online resource (XIV, 247 p. 85 illus.) |
| Disciplina | 004.678 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico |
Data mining
World Wide Web Medical informatics |
| ISBN | 3-540-89376-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | The First Workshop on Business Intelligence and Data Mining -- Moving Objects Databases Based on Dynamic Transportation Networks: Modeling, Indexing, and Implementation -- Approach to Detection of Community’s Consensus and Interest -- A Comparative Empirical Study on the Margin Setting of Stock Index Futures Calendar Spread Trading -- A Study on Multi-word Extraction from Chinese Documents -- Extracting Information from Semi-structured Web Documents: A Framework -- Discovering Interesting Classification Rules with Particle Swarm Algorithm -- International Workshop on Health Data Management -- Improving the Use, Analysis and Integration of Patient Health Data -- DM-Based Medical Solution and Application -- Learning-Function-Augmented Inferences of Causalities Implied in Health Data -- Support Vector Machine for Outlier Detection in Breast Cancer Survivability Prediction -- An Empirical Study of Combined Classifiers for Knowledge Discovery on Medical Data Bases -- Tracing the Application of Clinical Guidelines -- Doctoral Consortium on Data Engineering and Web Technology Research -- The Research on the Algorithms of Keyword Search in Relational Database -- An Approach to Monitor Scenario-Based Temporal Properties in Web Service Compositions -- Efficient Authentication and Authorization Infrastructure for Mobile Users -- An Effective Feature Selection Method Using the Contribution Likelihood Ratio of Attributes for Classification -- Unsupervised Text Learning Based on Context Mixture Model with Dirichlet Prior -- The Knowledge Discovery Research on User’s Mobility of Communication Service Provider -- Protecting Information Sharing in Distributed Collaborative Environment -- Relevance Feedback Learning for Web Image Retrieval Using Soft Support Vector Machine -- Feature Matrix Extraction and Classification of XML Pages -- Tuning the Cardinality of Skyline -- An HMM Approach to Anonymity Analysis of Continuous Mixes. |
| Record Nr. | UNISA-996465380403316 |
| Berlin, Germany : , : Springer, , [2008] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Database Systems for Advanced Applications : 29th International Conference, DASFAA 2024, Gifu, Japan, July 2–5, 2024, Proceedings, Part III / / edited by Makoto Onizuka, Jae-Gil Lee, Yongxin Tong, Chuan Xiao, Yoshiharu Ishikawa, Sihem Amer-Yahia, H. V. Jagadish, Kejing Lu
| Database Systems for Advanced Applications : 29th International Conference, DASFAA 2024, Gifu, Japan, July 2–5, 2024, Proceedings, Part III / / edited by Makoto Onizuka, Jae-Gil Lee, Yongxin Tong, Chuan Xiao, Yoshiharu Ishikawa, Sihem Amer-Yahia, H. V. Jagadish, Kejing Lu |
| Autore | Onizuka Makoto |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (853 pages) |
| Disciplina | 005.74 |
| Altri autori (Persone) |
LeeJae-Gil
TongYongxin XiaoChuan IshikawaYoshiharu Amer-YahiaSihem JagadishH. V LuKejing |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Machine learning
Database management Computers Computer networks Computers, Special purpose Application software Machine Learning Database Management System Computing Milieux Computer Communication Networks Special Purpose and Application-Based Systems Computer and Information Systems Applications |
| ISBN |
9789819755554
9819755557 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910983487303321 |
Onizuka Makoto
|
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Database Systems for Advanced Applications : 29th International Conference, DASFAA 2024, Gifu, Japan, July 2–5, 2024, Proceedings, Part II / / edited by Makoto Onizuka, Jae-Gil Lee, Yongxin Tong, Chuan Xiao, Yoshiharu Ishikawa, Sihem Amer-Yahia, H. V. Jagadish, Kejing Lu
| Database Systems for Advanced Applications : 29th International Conference, DASFAA 2024, Gifu, Japan, July 2–5, 2024, Proceedings, Part II / / edited by Makoto Onizuka, Jae-Gil Lee, Yongxin Tong, Chuan Xiao, Yoshiharu Ishikawa, Sihem Amer-Yahia, H. V. Jagadish, Kejing Lu |
| Autore | Onizuka Makoto |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (873 pages) |
| Disciplina | 005.74 |
| Altri autori (Persone) |
LeeJae-Gil
TongYongxin XiaoChuan IshikawaYoshiharu Amer-YahiaSihem JagadishH. V LuKejing |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Machine learning
Database management Computers Computer networks Computers, Special purpose Application software Machine Learning Database Management System Computing Milieux Computer Communication Networks Special Purpose and Application-Based Systems Computer and Information Systems Applications |
| ISBN |
9789819757794
9819757797 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910983322903321 |
|
Onizuka Makoto
|
||
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Database Systems for Advanced Applications : 29th International Conference, DASFAA 2024, Gifu, Japan, July 2–5, 2024, Proceedings, Part III / / edited by Makoto Onizuka, Jae-Gil Lee, Yongxin Tong, Chuan Xiao, Yoshiharu Ishikawa, Sihem Amer-Yahia, H. V. Jagadish, Kejing Lu
| Database Systems for Advanced Applications : 29th International Conference, DASFAA 2024, Gifu, Japan, July 2–5, 2024, Proceedings, Part III / / edited by Makoto Onizuka, Jae-Gil Lee, Yongxin Tong, Chuan Xiao, Yoshiharu Ishikawa, Sihem Amer-Yahia, H. V. Jagadish, Kejing Lu |
| Autore | Onizuka Makoto |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (853 pages) |
| Disciplina | 005.74 |
| Altri autori (Persone) |
LeeJae-Gil
TongYongxin XiaoChuan IshikawaYoshiharu Amer-YahiaSihem JagadishH. V LuKejing |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Machine learning
Database management Computers Computer networks Computers, Special purpose Application software Machine Learning Database Management System Computing Milieux Computer Communication Networks Special Purpose and Application-Based Systems Computer and Information Systems Applications |
| ISBN |
9789819755554
9819755557 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996641270503316 |
|
Onizuka Makoto
|
||
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Database Systems for Advanced Applications : 29th International Conference, DASFAA 2024, Gifu, Japan, July 2–5, 2024, Proceedings, Part II / / edited by Makoto Onizuka, Jae-Gil Lee, Yongxin Tong, Chuan Xiao, Yoshiharu Ishikawa, Sihem Amer-Yahia, H. V. Jagadish, Kejing Lu
| Database Systems for Advanced Applications : 29th International Conference, DASFAA 2024, Gifu, Japan, July 2–5, 2024, Proceedings, Part II / / edited by Makoto Onizuka, Jae-Gil Lee, Yongxin Tong, Chuan Xiao, Yoshiharu Ishikawa, Sihem Amer-Yahia, H. V. Jagadish, Kejing Lu |
| Autore | Onizuka Makoto |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (873 pages) |
| Disciplina | 005.74 |
| Altri autori (Persone) |
LeeJae-Gil
TongYongxin XiaoChuan IshikawaYoshiharu Amer-YahiaSihem JagadishH. V LuKejing |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Machine learning
Database management Computers Computer networks Computers, Special purpose Application software Machine Learning Database Management System Computing Milieux Computer Communication Networks Special Purpose and Application-Based Systems Computer and Information Systems Applications |
| ISBN |
9789819757794
9819757797 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996641269003316 |
|
Onizuka Makoto
|
||
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Database Systems for Advanced Applications : 29th International Conference, DASFAA 2024, Gifu, Japan, July 2–5, 2024, Proceedings, Part V / / edited by Makoto Onizuka, Jae-Gil Lee, Yongxin Tong, Chuan Xiao, Yoshiharu Ishikawa, Sihem Amer-Yahia, H. V. Jagadish, Kejing Lu
| Database Systems for Advanced Applications : 29th International Conference, DASFAA 2024, Gifu, Japan, July 2–5, 2024, Proceedings, Part V / / edited by Makoto Onizuka, Jae-Gil Lee, Yongxin Tong, Chuan Xiao, Yoshiharu Ishikawa, Sihem Amer-Yahia, H. V. Jagadish, Kejing Lu |
| Autore | Onizuka Makoto |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (562 pages) |
| Disciplina | 005.74 |
| Altri autori (Persone) |
LeeJae-Gil
TongYongxin XiaoChuan IshikawaYoshiharu Amer-YahiaSihem JagadishH. V LuKejing |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Machine learning
Database management Computers Computer networks Computers, Special purpose Application software Machine Learning Database Management System Computing Milieux Computer Communication Networks Special Purpose and Application-Based Systems Computer and Information Systems Applications |
| ISBN |
9789819755691
9819755697 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Natural language processing -- Large language model -- Time series and stream data. |
| Record Nr. | UNINA-9910917786303321 |
|
Onizuka Makoto
|
||
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Database Systems for Advanced Applications : 29th International Conference, DASFAA 2024, Gifu, Japan, July 2–5, 2024, Proceedings, Part VI / / edited by Makoto Onizuka, Jae-Gil Lee, Yongxin Tong, Chuan Xiao, Yoshiharu Ishikawa, Sihem Amer-Yahia, H. V. Jagadish, Kejing Lu
| Database Systems for Advanced Applications : 29th International Conference, DASFAA 2024, Gifu, Japan, July 2–5, 2024, Proceedings, Part VI / / edited by Makoto Onizuka, Jae-Gil Lee, Yongxin Tong, Chuan Xiao, Yoshiharu Ishikawa, Sihem Amer-Yahia, H. V. Jagadish, Kejing Lu |
| Autore | Onizuka Makoto |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (510 pages) |
| Disciplina | 006.31 |
| Altri autori (Persone) |
LeeJae-Gil
TongYongxin XiaoChuan IshikawaYoshiharu Amer-YahiaSihem JagadishH. V LuKejing |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Machine learning
Application software Computers Computer networks Computers, Special purpose Machine Learning Computer and Information Systems Applications Computing Milieux Computer Communication Networks Special Purpose and Application-Based Systems |
| ISBN | 981-9755-72-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents - Part VI -- Graph and Network -- Cascading Graph Convolution Contrastive Learning Networks for Multi-behavior Recommendation -- 1 Introduction -- 2 Related Work -- 3 Problem Definition -- 4 Proposed Model -- 4.1 Overall Framework -- 4.2 Node Representation Learning -- 4.3 Multi-task Learning -- 4.4 Contrastive Learning -- 4.5 Joint Optimization -- 5 Experiment -- 5.1 Experiment Settings -- 5.2 Overall Performance -- 5.3 Ablation Study -- 5.4 Hyper-parameter Study -- 6 Conclusion -- References -- Social Relation Enhanced Heterogeneous Graph Contrastive Learning for Recommendation -- 1 Introduction -- 2 Related Work -- 2.1 Social Recommendation -- 2.2 Heterogeneous Graph Learning -- 2.3 Contrastive Learning for Recommendation -- 3 Methodology -- 3.1 Definitions and Problem Formulation -- 3.2 Cross-View Heterogeneous Graph Construction -- 3.3 View-Based Graph Learning -- 3.4 View-Level Contrastive Learning -- 3.5 Multi-task Training -- 4 Experiment -- 4.1 Experimental Setting -- 4.2 Performance Comparision(RQ1) -- 4.3 Experiment with Effectiveness(RQ2) -- 4.4 Hyper-parameter Analysis(RQ3) -- 5 Conclusion -- References -- Higher-Order Graph Contrastive Learning for Recommendation -- 1 Introduction -- 2 Preliminaries -- 3 The Proposed Method -- 3.1 Construction of High-Order Graphs -- 3.2 Message Propagation and Knowledge Fusion -- 3.3 Contrastive Learning for High-Order View -- 3.4 Contrastive Learning for General View -- 3.5 Optimization -- 4 Experiments -- 4.1 Experimental Settings -- 4.2 Overall Performance Comparison -- 4.3 Further Analysis of HoGCL -- 5 Related Work -- 6 Conclusion -- References -- FNDPro: Evaluating the Importance of Propagations during Fake News Spread -- 1 Introduction -- 2 Related Work -- 2.1 Content-Based Models -- 2.2 Graph-Based Models -- 3 Methodology.
3.1 News Propagation Network -- 3.2 Propagation Encoder -- 3.3 Propagation Transformer Module -- 3.4 Learning and Optimization -- 4 Experiments -- 4.1 Main Results -- 4.2 Propagation Transformer Study -- 4.3 Discussion -- 4.4 Case Study -- 5 Conclusion -- References -- Leveraging Homophily-Augmented Energy Propagation for Bot Detection on Graphs -- 1 Introduction -- 2 Preliminaries and Problem Statement -- 3 Proposed Model -- 3.1 Impacts of Graph Structure on In-Distribution Learning -- 3.2 Heterophily-Wise Node Embedding Learning -- 3.3 Energy Calculation -- 3.4 Homophily-Augmented Energy Propagation -- 3.5 Loss Function -- 4 Experimental Results and Analysis -- 4.1 Experimental Setup -- 4.2 Effectiveness of Edge Prediction -- 4.3 Comparison with Baselines for Bot Detection -- 4.4 Case Study: ODD for Bot Detection -- 4.5 Ablation Study -- 5 Conclusion -- References -- Multi-level Contrastive Learning on Weak Social Networks for Information Diffusion Prediction -- 1 Introduction -- 2 Preliminaries -- 3 Methodology -- 3.1 Multiplex Heterogeneous Graph Learning -- 3.2 Self-supervised Graph Training -- 3.3 Information Diffusion Prediction -- 4 Performance Evaluation -- 4.1 Experimental Settings -- 4.2 Overall Performance (RQ1) -- 4.3 Ablation Study (RQ2) -- 4.4 Hyperparameter Analysis (RQ3) -- 4.5 Performance in Different Scenarios (RQ4) -- 5 Related Work -- 6 Conclusion -- References -- BiasRec: A General Bias-Aware Social Recommendation Model -- 1 Introduction -- 2 Related Work -- 2.1 Bias In Recommendation System -- 2.2 Social Recommendation -- 3 Proposed Method -- 3.1 Preliminaries and General Framework -- 3.2 Data Transformation -- 3.3 Representation Learning -- 3.4 Rating Prediction -- 3.5 Loss Function -- 4 Experiment -- 4.1 Experimental Settings -- 4.2 Experimental Results -- 4.3 Ablation Experiment -- 4.4 Bias vs. Preference -- 5 Conclusion. References -- Beyond the Known: Novel Class Discovery for Open-World Graph Learning -- 1 Introduction -- 2 Problem Formulation -- 3 Methodology -- 3.1 Prototypical Attention Network -- 3.2 Pseudo-Label Guided Open-World Learning -- 4 Experiments -- 4.1 Experiment Settings -- 4.2 Main Results -- 4.3 Abaltion Study -- 4.4 Impact of Hyper-Parameter Settings -- 5 Related Work -- 6 Conclusion -- References -- Robust Graph Recommendation via Noise-Aware Adversarial Perturbation -- 1 Introduction -- 2 Preliminary -- 3 Proposed Methods -- 3.1 Confidence-Score Weighted Interaction Graph -- 3.2 Noise-aware Adversarial Perturbation -- 3.3 Optimization -- 4 Experiments -- 4.1 Experiment Setup -- 4.2 Overall Performance (RQ1) -- 4.3 Robustness Evaluation (RQ2) -- 4.4 Ablation Study (RQ3) -- 4.5 Further Analysis (RQ4) -- 4.6 Parameter Sensitivity (RQ5) -- 5 Related Work -- 6 Conclusion -- References -- Learning Social Graph for Inactive User Recommendation -- 1 Introduction -- 2 Industrial Observations on Social Relation -- 3 Preliminary -- 4 The Proposed Model -- 4.1 Encoding User-Item Interactions -- 4.2 Graph Structure Learning on Social Graph -- 4.3 Mimic Learning -- 4.4 Complexity Analysis -- 5 Experiments -- 5.1 Experimental Setup -- 5.2 Overall Recommendation Performance(RQ1) -- 5.3 Effects of Graph Structure Learning(RQ2) -- 5.4 Effects of Hyper-Parameters(RQ3) -- 6 Related Work -- 7 Conclusion -- References -- MANE: A Multi-cascade Adversarial Network Embedding Model for Anchor Link Prediction -- 1 Introduction -- 2 Related Work -- 3 The MANE Model -- 3.1 Model Overview -- 3.2 Problem Definition -- 3.3 Multi-cascade Network Embedding -- 3.4 Training with Adversarial Network -- 3.5 Anchor Link Prediction -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Results -- 5 Conclusion -- References. uTransfer: Unified Transferability Metric Incorporating Heterogeneous User Data in Social Network -- 1 Introduction -- 2 Related Work -- 2.1 Similarity Measurement -- 2.2 Transferability Measurement -- 3 Methodology -- 3.1 Problem Formulation -- 3.2 Our Method: uTransfer -- 4 Experiments -- 4.1 Experimental Settings -- 4.2 Performance Comparison -- 5 Conclusion -- References -- GPSR: Graph Prompt for Session-Based Recommendation -- 1 Introduction -- 2 Related Work -- 2.1 Session-Based Recommender Systems -- 2.2 Graph Pretraining -- 3 The Proposed GPSR Method -- 3.1 Session Graph Construction -- 3.2 Graph Model Pretraining -- 3.3 Prompt and Finetuning -- 3.4 Next-Item Prediction and Algorithm Summary -- 4 Experiments -- 4.1 Experimental Settings -- 4.2 Performance Improvement over Non-Pretraining Counterpart -- 4.3 Comparison with Baseline Methods -- 4.4 Analysis on the Basis Vector Number -- 5 Conclusion -- References -- Guiding Graph Learning with Denoised Modality for Multi-modal Recommendation -- 1 Introduction -- 2 Related Work -- 2.1 Multi-modal Recommendation -- 2.2 Graph Denoising Network -- 3 Preliminary -- 3.1 Modality-Aware User-Item Graph -- 3.2 Task Formulation -- 4 Methodology -- 4.1 Masked Modality Feature AutoEncoder -- 4.2 Modality-Guided Structure Denoising Learning -- 4.3 Cross-Modal Contrastive Aggregation -- 4.4 Prediction and Optimization -- 5 Experiments -- 5.1 Experimental Setup -- 5.2 Overall Performance -- 5.3 Ablation Study -- 5.4 Hyper-parameter Analysis -- 6 Conclusion -- References -- Enhancing Multi-view Contrastive Learning for Graph Anomaly Detection -- 1 Introduction -- 2 Related Work -- 2.1 Graph Anomaly Detection -- 2.2 Graph Contrastive Learning -- 3 Problem Formulation -- 4 Method -- 4.1 Global View Generation and Contrast Element Sample -- 4.2 Contrastive Learning Module -- 4.3 Reconstruction Module. 4.4 Anomaly Detection Calculation -- 5 Experiments -- 5.1 Datasets -- 5.2 Experimental Settings -- 5.3 Result and Analysis -- 5.4 Ablation Study -- 5.5 Parameter Study -- 6 Conclusion -- References -- Global Route Planning for Large-Scale Requests on Traffic-Aware Road Network -- 1 Introduction -- 2 Related Work -- 2.1 Shortest Path Planning Algorithm -- 2.2 Global Route Planning Algorithm -- 3 Preliminaries -- 4 Global Path Optimization -- 4.1 Traffic Evaluation and Weight Update -- 4.2 Query Grouping -- 4.3 Initial Path Planning -- 4.4 Local Path Optimization -- 4.5 Iterative Optimization -- 5 Experimental Study -- 5.1 Experiment Settings -- 6 Conclusion -- References -- TransGAD: A Transformer-Based Autoencoder for Graph Anomaly Detection -- 1 Introduction -- 2 Related Work -- 2.1 Graph Neural Networks -- 2.2 Graph Anomaly Detection -- 2.3 Graph Transformer -- 3 Problem Formulation -- 4 Methodology -- 4.1 Neighborhood Representation Sequence -- 4.2 Transformer-Based Encoder -- 4.3 Attribute Decoder and Structure Decoder -- 4.4 Graph Anomaly Detection -- 5 Experiments -- 5.1 Dataset Description -- 5.2 Experimental Setup -- 5.3 Experimental Result -- 6 Conclusion -- References -- Unsupervised Node Clustering via Contrastive Hard Sampling -- 1 Introduction -- 2 Related Work -- 2.1 Node Clustering -- 2.2 Contrastive Learning -- 3 Problem Formulation and Preliminary -- 3.1 Graph Contrastive Learning -- 4 MeCole -- 4.1 Node-Level Fine-Grained Contrastive Learning -- 4.2 Augmentation Scheme -- 4.3 Model Overview -- 4.4 Feature Decoupling -- 4.5 Joint Learning Framework -- 4.6 Integrate Content Representations -- 4.7 Synthesizing Nodes and Contrastive Learning -- 4.8 Decoupled Cluster Module -- 4.9 Put Everything Together -- 5 Experiments -- 5.1 Experiment Results -- 5.2 Ablation Study -- 5.3 Discrepancy Functions -- 5.4 Integrate Contrastive Learning. 5.5 Sparse Graph. |
| Record Nr. | UNINA-9910886078403321 |
|
Onizuka Makoto
|
||
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Database Systems for Advanced Applications : 29th International Conference, DASFAA 2024, Gifu, Japan, July 2–5, 2024, Proceedings, Part V / / edited by Makoto Onizuka, Jae-Gil Lee, Yongxin Tong, Chuan Xiao, Yoshiharu Ishikawa, Sihem Amer-Yahia, H. V. Jagadish, Kejing Lu
| Database Systems for Advanced Applications : 29th International Conference, DASFAA 2024, Gifu, Japan, July 2–5, 2024, Proceedings, Part V / / edited by Makoto Onizuka, Jae-Gil Lee, Yongxin Tong, Chuan Xiao, Yoshiharu Ishikawa, Sihem Amer-Yahia, H. V. Jagadish, Kejing Lu |
| Autore | Onizuka Makoto |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (562 pages) |
| Disciplina | 005.74 |
| Altri autori (Persone) |
LeeJae-Gil
TongYongxin XiaoChuan IshikawaYoshiharu Amer-YahiaSihem JagadishH. V LuKejing |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Machine learning
Database management Computers Computer networks Computers, Special purpose Application software Machine Learning Database Management System Computing Milieux Computer Communication Networks Special Purpose and Application-Based Systems Computer and Information Systems Applications |
| ISBN |
9789819755691
9819755697 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Natural language processing -- Large language model -- Time series and stream data. |
| Record Nr. | UNISA-996635671503316 |
|
Onizuka Makoto
|
||
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Database Systems for Advanced Applications [[electronic resource] ] : DASFAA 2015 International Workshops, SeCoP, BDMS, and Posters, Hanoi, Vietnam, April 20-23, 2015, Revised Selected Papers / / edited by An Liu, Yoshiharu Ishikawa, Tieyun Qian, Sarana Nutanong, Muhammad Aamir Cheema
| Database Systems for Advanced Applications [[electronic resource] ] : DASFAA 2015 International Workshops, SeCoP, BDMS, and Posters, Hanoi, Vietnam, April 20-23, 2015, Revised Selected Papers / / edited by An Liu, Yoshiharu Ishikawa, Tieyun Qian, Sarana Nutanong, Muhammad Aamir Cheema |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (XIV, 328 p. 99 illus.) |
| Disciplina | 005.74 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico |
Database management
Data mining Information storage and retrieval Application software Algorithms Database Management Data Mining and Knowledge Discovery Information Storage and Retrieval Information Systems Applications (incl. Internet) Algorithm Analysis and Problem Complexity |
| ISBN | 3-319-22324-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Message from the Workshop Chairs -- Message from the Poster Chairs -- DASFAA 2015 Workshop Organizers -- DASFAA 2015 Posters Organizers -- Contents -- The Second International Workshop on Semantic Computing and Personalization (SeCoP) -- A Novel Method for Clustering Web Search Results with Wikipedia Disambiguation Pages -- 1 Introduction -- 2 Related Work -- 3 Problem Formulation -- 4 Method -- 4.1 Construction of Clustering Structure -- 4.2 Assignment of Search Results -- 5 Experiments and Results -- 5.1 Datasets -- 5.2 Measurements -- 5.3 Results -- 6 Conclusions -- References -- Integrating Opinion Leader and User Preference for Recommendation -- 1 Introduction -- 2 Related Work -- 3 The OLrs method -- 3.1 Preliminaries -- 3.2 Identifying Opinion Leaders -- 3.3 Predicting -- 4 Evaluation -- 4.1 Data Acquisition -- 4.2 Evaluation Metrics -- 4.3 Experimental Settings -- 4.4 Results and Analysis -- 5 Conclusions and Future Works -- References -- Learning Trend Analysis and Prediction Based on Knowledge Tracing and Regression Analysis -- Abstract -- 1 Introduction -- 2 Related Work -- 2.1 Knowledge Tracing Model -- 2.2 Post-Test Score Prediction -- 3 Problem Analysis -- 4 Algorithm Design -- 4.1 Course Structure Definition -- 4.2 Knowledge Tracing -- 4.3 Regression Modeling -- 4.4 Trend Analysis and Learning Prediction -- 5 Experiment Design and Results Analysis -- 5.1 Experiment Data Selection -- 5.2 Experiment Design -- 5.3 Results and Analysis -- 6 Conclusion -- References -- Intensive Maximum Entropy Model for Sentiment Classification of Short Text -- 1 Introduction -- 2 Related Work -- 3 Maximum Entropy Model via Intensive Feature Functions -- 3.1 Problem Definition -- 3.2 Intensive Maximum Entropy Model -- 3.3 Parameter Estimation -- 4 Experiments -- 4.1 Data Set -- 4.2 Influence of the Number of Iterations.
4.3 Comparison with Baselines -- 5 Conclusion -- References -- Maintaining Ranking Lists in Dynamic Virtual Environments -- 1 Introduction -- 2 Continuously Ranking List Maintenance -- 2.1 Preference Query by Global Ranking Lists -- 2.2 Preference Query by Brute Force -- 3 A Solution of CRL -- 3.1 Maintaining the Perceiving Relationships -- 3.2 Continuous Query Processing -- 3.3 Upper Bound the Interest Scores -- 3.4 Effective Size of Materialized Item Lists -- 4 Performance Evaluation -- 4.1 Experimental Settings -- 4.2 Results -- 5 Related Work -- 6 Conclusion -- References -- Knowledge Communication Analysis Based on Clustering and Association Rules Mining -- 1 Introduction -- 2 Related Work -- 3 Knowledge Communication Analysis Framework -- 3.1 Clustering Analysis -- 3.2 Association Rule Mining -- 4 Experiments -- 4.1 Data Set -- 4.2 Clustering Analysis for Knowledge Sources -- 4.3 Clustering Analysis for Knowledge Diffusion -- 4.4 Association Rule Mining for Knowledge Sources -- 4.5 Association Rule Mining for Knowledge Diffusion -- 5 Conclusion -- References -- Sentiment Detection of Short Text via Probabilistic Topic Modeling -- 1 Introduction -- 2 Related Work -- 2.1 Sentiment Detection -- 2.2 Short Text Classification -- 2.3 Latent Semantic Analysis -- 3 Short Text Sentiment Detection -- 3.1 Probabilistic Topic Modeling -- 3.2 Sentiment Detection with Topic-Based Similarity -- 4 Experiments -- 4.1 Data Set -- 4.2 Parameters -- 4.3 Results and Analysis -- 5 Conclusion -- References -- Schema Matching Based on Source Codes -- 1 Introduction -- 2 A General Framework for Schema Matching Based on Source Codes -- 2.1 Extracting Exterior Schemas -- 2.2 Evaluating the Quality of Matching -- 2.3 Finding the Optimal Mapping -- 3 Related Work -- 4 Conclusions -- References. A Quota-Based Energy Consumption Management Method for Organizations Using Nash Bargaining Solution -- 1 Introduction -- 2 Energy Consumption Satisfaction Degree -- 3 The Proposed NBS-based Energy Allocation Scheme -- 4 Numerical Simulation -- 5 Conclusion -- References -- Entity Relation Mining in Large-Scale Data -- 1 Introduction -- 2 Related Works -- 3 The Proposed Framework -- 3.1 Acquiring the Entity-Relationship Patterns -- 3.2 Extracting the Entity-Relationship Pairs -- 3.3 Evaluation of the Candidate Relationship Pairs -- 4 Implement of Distributed System -- 5 Experiments -- 5.1 Dataset -- 5.2 Results of Comparison -- 6 Conclusion -- References -- A Collaborative Filtering Model for Personalized Retweeting Prediction -- 1 Introduction -- 2 Related Work -- 2.1 Collaborative Filtering and Recommender Systems -- 2.2 Personalized Retweeting Prediction -- 3 Proposed Method -- 3.1 Latent Factor Model -- 3.2 Ranking -- 3.3 Decomposing Tweets -- 3.4 Attributes of Tweets in Latent Factor Model -- 3.5 Linear Combination of Latent Factors -- 4 Experiments -- 4.1 Data Set -- 4.2 Data Preprocess -- 4.3 Metrics -- 4.4 Comparison -- 4.5 Influence of Parameters -- 5 Conclusions -- References -- Finding Paraphrase Facts Based on Coordinate Relationships -- 1 Introduction -- 2 Related Work -- 2.1 Semantic Relation Extraction -- 2.2 Paraphrase Acquisition -- 3 Preliminaries -- 4 Basic Idea -- 5 Our Method -- 5.1 Template Extraction -- 5.2 Entity Tuple Extraction -- 5.3 The Mutual Reinforcement Algorithm -- 6 Evaluation -- 6.1 Experimental Setting -- 6.2 Results -- 7 Conclusion -- References -- The Second International Workshop on Big Data Management and Service (BDMS) -- Emergency Situation Awareness During Natural Disasters Using Density-Based Adaptive Spatiotemporal Clustering -- 1 Introduction -- 2 Related Work. 3 (, )-Density-based Adaptive Spatiotemporal Clusters -- 3.1 Data Model -- 3.2 Density-Based Spatiotemporal Adaptive Criteria -- 3.3 Definitions -- 3.4 (, )-Density-based Adaptive Spatiotemporal Cluster -- 4 Proposed Method -- 4.1 Concept and System Overview -- 4.2 Naive Bayes Classifier -- 4.3 Incremental Algorithm -- 5 Experimental Result -- 6 Conclusion -- References -- Distributed Data Managing in Health Care Social Network Based on Mobile P2P -- Abstract -- 1 Introduction -- 2 Methods -- 2.1 Workflow of Health Workers -- 2.2 Multi-Platform P2P Ad Hoc Network -- 2.3 Social Network and Distributed Data Storage -- 3 Results -- 4 Conclusions -- References -- Survey of MOOC Related Research -- 1 Introduction -- 2 Basic Research of Recent MOOC -- 3 MOOC Research Organizations -- 3.1 MOOC Research Organizations in Educational Area -- 3.2 MOOC Research Organizations in Computer Science Area -- 3.3 MOOC Research Organizations Combining both Education and Computer Science -- 4 Summary -- References -- Modeling Large Time Series for Efficient Approximate Query Processing -- 1 Introduction -- 2 Model-Based Database System Concept -- 3 Model Querying for Time Series Data -- 3.1 Model Construction -- 3.2 Query Computation over Models -- 4 Evaluation -- 4.1 AVG and SUM Queries -- 4.2 Histogram Query -- 5 Related Work -- 6 Conclusion and Future Work -- References -- Personalized User Value Model and Its Application -- 1 Introduction -- 2 Related Works -- 3 Five-Dimension Personalized User Value Model -- 3.1 User Input-Output Ratio Model -- 3.2 User Behavior Value Model -- 3.3 User Net Present Value Model -- 3.4 Five-Dimension Personalized User Value Contribution -- 4 Experiments -- References -- Posters -- Flexible Aggregation on Heterogeneous Information Networks -- 1 Introduction -- 2 Preliminaries -- 3 Aggregation Algorithm -- 4 Experiments Evaluation. 5 Conclusions -- References -- Discovering Organized POI Groups in a City -- 1 Introduction -- 2 Problem and Approach -- 2.1 Definition of Hybrid Similarity -- 2.2 Algorithm for Discovering OPGs -- 2.3 Algorithm for Classification -- 3 Visualization -- 4 Conclusions -- References -- Multi-roles Affiliation Model for General User Profiling -- 1 Introduction -- 2 Model -- 3 Inference -- 3.1 Update of Link Factors -- 3.2 Update of Attributes Affiliation Graph A -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Results and Discussion -- 5 Conclusion -- References -- Needle in a Haystack: Max/Min Online Aggregation in the Cloud -- 1 Introduction -- 2 Related Work -- 3 Overview -- 4 Randomization of Blocks -- 5 Query Processing -- 5.1 Estimation of Max/Min Value -- 5.2 Error Correction -- 6 Max/Min Online Aggregation in the Cloud -- 7 Performance Evaluation -- 7.1 Experiment Overview -- 7.2 Performance over Real Data -- 7.3 Query Error -- 8 Conclusion -- References -- FFD-Index: An Efficient Indexing Scheme for Star Subgraph Matching on Large RDF Graphs -- 1 Introduction -- 2 FFD-Index and Query Processing -- 3 Verification -- 4 Experiments -- 5 Conclusion -- References -- Leveraging Interactive Knowledge and Unlabeled Data in Gender Classification with Co-training -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Gender Classification with Co-training -- 4 Experimentation -- 5 Conclusion -- References -- Interactive Gender Inference in Social Media -- Abstract -- 1 Introduction -- 2 Related Work -- 3 A Two-Stage Approach -- 3.1 Stage 1: Four-Category Classification -- 3.2 Stage 2: Global Label Optimization -- 4 Experimentation -- 5 Conclusion -- References -- Joint Sentiment and Emotion Classification with Integer Linear Programming -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Joint Sentiment and Emotion Classification -- 4 Experimentation. 5 Conclusion. |
| Record Nr. | UNISA-996215642503316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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