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Titlebook: Database Systems for Advanced Applications. DASFAA 2021 International Workshops; BDQM, GDMA, MLDLDSA, Christian S. Jensen,Ee-Peng Lim,Chih-

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書目名稱Database Systems for Advanced Applications. DASFAA 2021 International Workshops
副標題BDQM, GDMA, MLDLDSA,
編輯Christian S. Jensen,Ee-Peng Lim,Chih-Ya Shen
視頻videohttp://file.papertrans.cn/264/263443/263443.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Database Systems for Advanced Applications. DASFAA 2021 International Workshops; BDQM, GDMA, MLDLDSA, Christian S. Jensen,Ee-Peng Lim,Chih-
描述.This volume constitutes the papers of several workshops which were held in conjunction with the 26th International Conference on Database Systems for Advanced Applications, DASFAA 2021, held in Taipei, Taiwan, in April 2021..The 29 revised full papers presented in this book were carefully reviewed and selected from 84 submissions.?..DASFAA 2021 presents the following five workshops:.6th International Workshop on Big Data Quality Management (BDQM 2021).5th International Workshop on Graph Data Management and Analysis (GDMA 2021). First International Workshop on Machine Learning and Deep Learning for Data Security Applications (MLDLDSA 2021).6th International Workshop on Mobile Data Management, Mining, and Computing on Social Network (MobiSocial 2021).2021 International Workshop on Mobile Ubiquitous Systems and Technologies (MUST 2021).Due to the Corona pandemic this event was held virtually..
出版日期Conference proceedings 2021
關鍵詞big data; graph data management; spatial data management; temporal data management; data mining; machine
版次1
doihttps://doi.org/10.1007/978-3-030-73216-5
isbn_softcover978-3-030-73215-8
isbn_ebook978-3-030-73216-5Series 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 Switzerl
The information of publication is updating

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LAA: Inductive Community Detection Algorithm Based on Label Aggregationool for network analysis. However, the existing approaches are transductive, even for original networks with structures or attributes changed, retraining was required to get the results. The rapid changes and explosive growth of information makes real-world application have great expectations for in
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Modeling and Querying Similar Trajectory in Inconsistent Spatial Datant spatial data. We develop a framework for querying similar trajectories inconsistent spatial data. For any given entity, our method will provide a way to query its similar trajectories in the inconsistent spatial data. We propose a dynamic programming algorithm and a threshold filter for probabili
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NREngine: A Graph-Based Query Engine for Network Reachability paper, we propose a query engine called . for network reachability when considering the network security policies. NREngine constructs a knowledge graph based on the network security policies and designs an algorithm over the graph for the network reachability. Furthermore, for supporting a user-fr
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