NDLI: Efficient keyword search for smallest LCAs in XML databases

Content Provider	ACM Digital Library
Author	Papakonstantinou, Yannis Xu, Yu
Abstract	Keyword search is a proven, user-friendly way to query HTML documents in the World Wide Web. We propose keyword search in XML documents, modeled as labeled trees, and describe corresponding efficient algorithms. The proposed keyword search returns the set of smallest trees containing all keywords, where a tree is designated as "smallest" if it contains no tree that also contains all keywords. Our core contribution, the Indexed Lookup Eager algorithm, exploits key properties of smallest trees in order to outperform prior algorithms by orders of magnitude when the query contains keywords with significantly different frequencies. The Scan Eager variant is tuned for the case where the keywords have similar frequencies. We analytically and experimentally evaluate two variants of the Eager algorithm, along with the Stack algorithm [13]. We also present the XKSearch system, which utilizes the Indexed Lookup Eager, Scan Eager and Stack algorithms and a demo of which on DBLP data is available at http://www.db.ucsd.edu/projects/xksearch. Finally, we extend the Indexed Lookup Eager algorithm to answer Lowest Common Ancestor (LCA) queries.
Starting Page	527
Ending Page	538
Page Count	12
File Format	PDF
ISBN	1595930604
DOI	10.1145/1066157.1066217
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2005-06-14
Publisher Place	New York
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

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Efficient keyword search for smallest LCAs in XML databases