TY  - BOOK
AU  - Zhang,Wenjie
AU  - Tung,Anthony
AU  - Zheng,Zhonglong
AU  - Yang,Zhengyi
AU  - Wang,Xiaoyang
AU  - Guo,Hongjie
ED  - SpringerLink (Online service)
TI  - Web and Big Data: 8th International Joint Conference, APWeb-WAIM 2024, Jinhua, China, August 30 - September 1, 2024, Proceedings, Part III 
T2  - Lecture Notes in Computer Science,
SN  - 9789819772384
AV  - QA76.9.B45 
U1  - 005.7 23
PY  - 2024///
CY  - Singapore
PB  - Springer Nature Singapore, Imprint: Springer
KW  - Big data
KW  - Data structures (Computer science)
KW  - Information theory
KW  - Application software
KW  - Image processing
KW  - Digital techniques
KW  - Computer vision
KW  - Data mining
KW  - Big Data
KW  - Data Structures and Information Theory
KW  - Computer and Information Systems Applications
KW  - Computer Imaging, Vision, Pattern Recognition and Graphics
KW  - Data Mining and Knowledge Discovery
N1  -  -- Spatial and Temporal Data.  -- Temporalformer: A Temporal Decomposition Causal Transformer Network For Wind Power Forecasting.  -- MSCFNet: A Multi-Scale Spatial and Channel Fusion Network for Geological Environment Remote Sensing Interpreting.  -- TS-HCL: Hierarchical Layer-wise Contrastive Learning for Unsupervised Domain Adaptation on Time-Series.  -- Dynamic-Static Fusion for Spatial-Temporal Anomaly Detection and Interpretation in Multivariate Time Series.  -- MFCD:A deep learning method with fuzzy clustering for time series anomaly detection.  -- Graph Neural Network.  -- SBGMN: A Multi-View Sign Prediction Network for Bipartite Graphs.  -- Product Anomaly Detection on Heterogeneous Graphs with Sparse Labels.  -- Generic and Scalable Detection of Risky Transactions Using Density Flows: Applications to Financial Networks.  -- Attributed Heterogeneous Graph Embedding with Meta-graph Attention.  -- Automated Multi-scale Contrastive Learning with Sample-awareness for Graph Classification.  -- CGAR: A Contrastive Graph Attention Residual Network for Enhanced Fake News Detection.  -- GCH: Graph contrastive Learning with Higher-order Networks.  -- LPRL-GCNN for Multi-Relation Link Prediction in Education.  -- Multi-view Graph Neural Network for Fair Representation Learning.  -- MERGE: Multi-View Relationship Graph Network for Event-Driven Stock Movement Prediction.  -- Relation-Aware Heterogeneous Graph Neural Network for Fraud Detection.  -- Graph Mining.  -- Robust Local Community Search over Large Heterogeneous Information Networks.  -- Community discovery in social network via dual-technique.  -- CSGTM: Capsule Semantic Graph-Guided Latent Community Topics Discovery.  -- Efficient (α, β, γ)-Core Search in Bipartite Graphs Based on Bi-triangles.  -- Identifying Rank-happiness Maximizing Sets under Group Fairness Constraints.  -- Reachability-Aware Fair Influence Maximization.  -- Towards Efficient Heuristic Graph Edge Coloring.  -- Tree and Graph based Two-Stages Routing for Approximate Nearest Neighbor Search.  -- Unbiasedly Estimate Temporal Katz Centrality and Identify Top-K Vertices in Streaming Graph.  -- Database System and Query Optimization.  -- Gar++: Natural Language to SQL Translation with Efficient Generate-and-Rank.  -- A Composable Architecture for Cloud Transactional DBMS.  -- Computing Minimum Subset Repair On Incomplete Data.  -- Flutist: Parallelizing Transaction Processing for LSM-tree-based Relational Database.  -- Poplar: Partially-Ordered Parallel Logging for Lower Isolation Levels.  -- Table Embedding Models Based on Contrastive Learning for Improved Cardinality Estimation
N2  - The five-volume set LNCS 14961, 14962, 14963, 14964 and 14965 constitutes the refereed proceedings of the 8th International Joint Conference on Web and Big Data, APWeb-WAIM 2024, held in Jinhua, China, during August 30-September 1, 2024. The 171 full papers presented in these proceedings were carefully reviewed and selected from 558 submissions. The papers are organized in the following topical sections: Part I: Natural language processing, Generative AI and LLM, Computer Vision and Recommender System. Part II: Recommender System, Knowledge Graph and Spatial and Temporal Data. Part III: Spatial and Temporal Data, Graph Neural Network, Graph Mining and Database System and Query Optimization. Part IV: Database System and Query Optimization, Federated and Privacy-Preserving Learning, Network, Blockchain and Edge computing, Anomaly Detection and Security Part V: Anomaly Detection and Security, Information Retrieval, Machine Learning, Demonstration Paper and Industry Paper
UR  - http://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-981-97-7238-4
ER  -