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Discovering graph functional dependencies

  • University of Edinburgh
  • Beihang University
  • Harbin Institute of Technology

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

This paper studies discovery of GFDs, a class of functional dependencies defined on graphs. We investigate the fixed-parameter tractability of three fundamental problems related to GFD discovery. We show that the implication and satisfiability problems are fixed-parameter tractable, but the validation problem is co-W[1]-hard. We introduce notions of reduced GFDs and their topological support, and formalize the discovery problem for GFDs. We develop algorithms for discovering GFDs and computing their covers. Moreover, we show that GFD discovery is feasible over large-scale graphs, by providing parallel scalable algorithms for discovering GFDs that guarantee to reduce running time when more processors are used. Using real-life and synthetic data, we experimentally verify the effectiveness and scalability of the algorithms.

源语言英语
主期刊名SIGMOD 2018 - Proceedings of the 2018 International Conference on Management of Data
编辑Gautam Das, Christopher Jermaine, Ahmed Eldawy, Philip Bernstein
出版商Association for Computing Machinery
427-439
页数13
ISBN(电子版)9781450317436
DOI
出版状态已出版 - 27 5月 2018
活动44th ACM SIGMOD International Conference on Management of Data, SIGMOD 2018 - Houston, 美国
期限: 10 6月 201815 6月 2018

出版系列

姓名Proceedings of the ACM SIGMOD International Conference on Management of Data
ISSN(印刷版)0730-8078

会议

会议44th ACM SIGMOD International Conference on Management of Data, SIGMOD 2018
国家/地区美国
Houston
时期10/06/1815/06/18

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