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Query ranking in probabilistic XML data
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Source Extending Database Technology; Vol. 360 archive
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology table of contents
Saint Petersburg, Russia
SESSION: Research sessions: XML, XPath, XQuery table of contents
Pages 156-167  
Year of Publication: 2009
ISBN:978-1-60558-422-5
Authors
Lijun Chang  The Chinese University of Hong Kong, Hong Kong, China
Jeffrey Xu Yu  The Chinese University of Hong Kong, Hong Kong, China
Lu Qin  The Chinese University of Hong Kong, Hong Kong, China
Publisher
ACM  New York, NY, USA
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ABSTRACT

Twig queries have been extensively studied as a major fragment of XPATH queries to query XML data. In this paper, we study PXML-RANK query, (Q, k), which is to rank top-k probabilities of the answers of a twig query Q in probabilistic XML (PXML) data. A new research issue is how to compute top-k probabilities of answers of a twig query Q in PXML in the presence of containment (ancestor/descendant) relationships. In the presence of the ancestor/descendant relationships, the existing dynamic programming approaches to rank top-k probabilities over a set of tuples cannot be directly applied, because any node/edge in PXML may have impacts on the top-k probabilities of answers. We propose new algorithms to compute PXML-RANK queries efficiently and give conditions under which a PXML-RANK query can be processed efficiently without enumeration of all the possible worlds. We conduct extensive performance studies using both real and large benchmark datasets, and confirm the efficiency of our algorithms.


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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Collaborative Colleagues:
Lijun Chang: colleagues
Jeffrey Xu Yu: colleagues
Lu Qin: colleagues