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Effective keyword search for valuable lcas over xml documents
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Conference on Information and Knowledge Management archive
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management table of contents
Lisbon, Portugal
SESSION: XML query processing (DB) table of contents
Pages 31-40  
Year of Publication: 2007
ISBN:978-1-59593-803-9
Authors
Guoliang Li  Tsinghua University, Beijing, China
Jianhua Feng  Tsinghua University, Beijing, China
Jianyong Wang  Tsinghua University, Beijing, China
Lizhu Zhou  Tsinghua University, Beijing, China
Sponsors
SIGIR: ACM Special Interest Group on Information Retrieval
SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 14,   Downloads (12 Months): 125,   Citation Count: 12
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ABSTRACT

In this paper, we study the problem of effective keyword search over XML documents. We begin by introducing the notion of Valuable Lowest Common Ancestor (VLCA) to accurately and effectively answer keyword queries over XML documents. We then propose the concept of Compact VLCA (CVLCA) and compute the meaningful compact connected trees rooted as CVLCAs as the answers of keyword queries. To efficiently compute CVLCAs, we devise an effective optimization strategy for speeding up the computation, and exploit the key properties of CVLCA in the design of the stack-based algorithm for answering keyword queries. We have conducted an extensive experimental study and the experimental results show that our proposed approach achieves both high efficiency and effectiveness when compared with existing proposals.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  12

Collaborative Colleagues:
Guoliang Li: colleagues
Jianhua Feng: colleagues
Jianyong Wang: colleagues
Lizhu Zhou: colleagues