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Fast evaluation of structured queries for information retrieval
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Source Annual ACM Conference on Research and Development in Information Retrieval archive
Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval table of contents
Seattle, Washington, United States
Pages: 30 - 38  
Year of Publication: 1995
ISBN:0-89791-714-6
Author
Eric W. Brown  Computer Science Department, University of Massachusetts, Amherst, MA
Sponsors
BCS-ISRG : BCS-ISRG
CEPIS : Council of European Professional Informatics Societies
AICA : Assoc Italianai de Calcolo Automatico
BCS-IRSG : BCS/Information Retrieval Specialist Group
German Comp Soc : GI - Gesellshaft for Informatik
IPSJ : Information Processing Society of Japan
SIGIR: ACM Special Interest Group on Information Retrieval
DD :
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 9,   Downloads (12 Months): 66,   Citation Count: 26
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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