NDLI: Bloom filter-based keyword search over XML data in structured Peer-to-Peer systems

Content Provider	IEEE Xplore Digital Library
Author	Weimin He Teng Lv
Copyright Year	2010
Description	Author affiliation: Department of Computing and New Media Technologies, University of Wisconsin-Stevens Point, USA (Weimin He) \|\| Teaching and Research Section of Computer, Artillery Academy, Hefei, Anhui, China (Teng Lv)
Abstract	With the popularity of Extensible Markup Language (XML) as the new standard of data exchange on the web, a large number of data sources are represented or encoded in XML format. Therefore, querying and searching XML data on the web has attracted much attention in the database literature. The new emerging Peer-to-Peer (P2P) computing model has fueled the autonomous data sharing over the Internet in a more flexible fashion. Needless to say, XML data retrieval in P2P systems has become attractive to professionals in both research and industrial communities. In this paper, we propose a Bloom-Filter based keyword search framework for XML data retrieval in structured P2P systems. We designed an efficient Bloom-Filter based XML indexing scheme for XML data retrieval in structured P2P systems. We also developed an effective keyword search algorithm over our Bloom-Filter encoded XML indexes. The experimental results demonstrate that our novel indexing scheme is much more efficient compared to the traditional full-indexing scheme, our keyword search algorithm is efficient in terms of query response time, and our system is scalable in terms of data size and network size.
Starting Page	177
Ending Page	181
File Size	1111459
Page Count	5
File Format	PDF
ISBN	9781424455379
e-ISBN	9781424455409
DOI	10.1109/ICCSIT.2010.5564065
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-09
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Q measurement XML Database Peer-to-Peer Books Indexing
Content Type	Text
Resource Type	Article

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