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ABSTRACT
Information retrieval systems are being challenged to manage
larger and larger document collections. In an effort to provide
better retrieval performance on large collections, more
sophisticated retrieval techniques have been developed that support
rich, structured queries. Structured queries are not amenable to
previously proposed optimization techniques. Optimizing execution,
however, is even more important in the context of large document
collections. We present a new structured query optimization
technique which we have implemented in an inference network-based
information retrieval system. Experimental results show that query
evaluation time can be reduced by more than half with little impact
on retrieval effectiveness.
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 26
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Sihem Amer-Yahia , Mary Fernández , Divesh Srivastava , Yu Xu, Phrase Matching in XML, Proceedings of the 29th international conference on Very large data bases, p.177-188, September 09-12, 2003, Berlin, Germany
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