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Titlebook: Web and Big Data; 7th International Jo Xiangyu Song,Ruyi Feng,Geyong Min Conference proceedings 2024 The Editor(s) (if applicable) and The

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發(fā)表于 2025-3-21 19:02:42 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Web and Big Data
副標(biāo)題7th International Jo
編輯Xiangyu Song,Ruyi Feng,Geyong Min
視頻videohttp://file.papertrans.cn/1022/1021664/1021664.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Web and Big Data; 7th International Jo Xiangyu Song,Ruyi Feng,Geyong Min Conference proceedings 2024 The Editor(s) (if applicable) and The
描述.The 4-volume set LNCS 14331, 14332, 14333, and 14334 constitutes the refereed proceedings of the 7th International Joint Conference, APWeb-WAIM 2023, which took place in Wuhan, China, in October 2023...The total of 138 papers included in the proceedings were carefully reviewed and selected from 434 submissions. They focus on?innovative ideas, original research findings, case study results, and experienced insights in the areas of the World Wide Web and big data, covering Web technologies, database systems, information management, software engineering, knowledge graph, recommend system and big data..
出版日期Conference proceedings 2024
關(guān)鍵詞computer networks; computer security; data mining; information retrieval; machine learning; network proto
版次1
doihttps://doi.org/10.1007/978-981-97-2303-4
isbn_softcover978-981-97-2302-7
isbn_ebook978-981-97-2303-4Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

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,A BERT-Based Semantic Enhanced Model for?COVID-19 Fake News Detection,eos. Meanwhile, fake news spreads widely on the Internet, preventing authoritative information from spreading and hindering the fight against the disease. To detect and recognize fake news, as well as to prevent its spread, effective detection models are urgently required. Text information is the mo
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,Mining Frequent Geo-Subgraphs in?a?Knowledge Graph,ial networks, citation networks, protein interaction networks, etc. This paper studies frequent subgraph mining in a knowledge graph, where some vertices are associated with geo-coordinates, called geo-vertices. We introduce geo-constraints and propose the problem of frequent geo-subgraph (FGS) mini
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,Locality Sensitive Hashing for?Data Placement to?Optimize Parallel Subgraph Query Evaluation, an opportunity for parallelizing subgraph queries in large graphs. To effectively evaluate these subgraph queries, it is crucial to place vertices among different workers. In contrast to widely used hash-based techniques, our approach leverages the utilization of locality sensitive hashing methods
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DUTD: A Deeper Understanding of Trajectory Data for User Identity Linkage, studies on users’ spatio-temporal behaviors. Among these studies, the task of trajectory-based user identity linkage (UIL) has attracted extensive attention recently. Existing efforts for the task mainly rely on data mining methods and sequence models to extract features and measure user identity s
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