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Distributed SLCA-based XML keyword search by map-reduce

  • Shanghai Ocean University
  • Fudan University

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Large scales of XML information comes continually from new Web applications, and SLCA (Smallest Lowest Common Ancestor)-based XML keyword search is one of the most important information retrieval approaches. Previous approaches focus on building index for XML documents. However in information dissemination scenario, it is impossible to build index in advance for continuous XML document streams. This paper addresses SLCA-based keyword search for continuous XML documents by Map-Reduce mechanism. We use parallel algorithms to process plenty of XML documents in Hadoop environment. A distributed SLCA computation method is designed, where each net node computes SLCA independently and just a little information needs be transmitted. A real Hadoop environment is built and we demonstrate the efficiency of our algorithms analytically and experimentally.

源语言英语
主期刊名Database Systems for Advanced Applications - 15th International Conference, DASFAA 2010, International Workshops
主期刊副标题GDM, BenchmarX, MCIS, SNSMW, DIEW, UDM, Revised Selected Papers
386-397
页数12
DOI
出版状态已出版 - 2010
活动15th International Conference on Database Systems for Advanced Applications, DASFAA 2010 - Tsukuba, 日本
期限: 1 4月 20104 4月 2010

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
6193 LNCS
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议15th International Conference on Database Systems for Advanced Applications, DASFAA 2010
国家/地区日本
Tsukuba
时期1/04/104/04/10

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