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Towards bipartite graph data management

  • East China Normal University
  • Nanjing Normal University

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Bipartite graphs are widely used to model social networks and web data. However bipartite graph data management (BGDM for short) is not fully studied. Without appropriate indexing structures, query and analysis operations on bipartite graphs are not efficient. In this paper, we raise the issues of BGDM and present architecture of BGDM. Then we propose a logic graph structure (i.e., star) for indexing bipartite graph to improve common operations efficiently. Furthermore, we propose a star-based block structure to store bipartite graphs and the relevant query algorithm. The star-based method may avoid loading the whole block for vertex queries using Bloom filter. Finally, our experiments show that the block design is effective and feasible for vertex query algorithm.

源语言英语
主期刊名Proceedings of the 2nd International Workshop on Cloud Data Management, CloudDB'10, Co-located with 19th International Conference on Information and Knowledge Management, CIKM'10
57-66
页数10
DOI
出版状态已出版 - 2010
活动2nd International Workshop on Cloud Data Management, CloudDB'10, Co-located with 19th International Conference on Information and Knowledge Management, CIKM'10 - Toronto, ON, 加拿大
期限: 26 10月 201030 10月 2010

出版系列

姓名International Conference on Information and Knowledge Management, Proceedings

会议

会议2nd International Workshop on Cloud Data Management, CloudDB'10, Co-located with 19th International Conference on Information and Knowledge Management, CIKM'10
国家/地区加拿大
Toronto, ON
时期26/10/1030/10/10

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