A parallel relational database management system approach to relevance feedback in information retrieval

A scalable, parallel, relational database‐driven information retrieval engine is described. To support portability across a wide‐range of execution environments, including parallel machines, all algorithms strictly adhere to the SQL‐92 standard. By incorporating relevance feedback algorithms, accura...

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Bibliographic Details
Published in:Journal of the American Society for Information Science Vol. 50; no. 5; pp. 413 - 426
Main Authors: Lundquist, Carol, Frieder, Ophir, Holmes, David O., Grossman, David
Format: Journal Article
Language:English
Published: New York John Wiley & Sons, Inc 1999
John Wiley & Sons
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ISSN:0002-8231, 1097-4571
Online Access:Get full text
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Summary:A scalable, parallel, relational database‐driven information retrieval engine is described. To support portability across a wide‐range of execution environments, including parallel machines, all algorithms strictly adhere to the SQL‐92 standard. By incorporating relevance feedback algorithms, accuracy is enhanced over prior database‐driven information retrieval efforts. Algorithmic modifications to our earlier prototype resulted in significantly enhanced scalability. Currently our information retrieval engine sustains near‐linear speedups using a 24‐node parallel database machine. Experiments using the TIPSTER data collections are presented to validate the described approaches.
Bibliography:ArticleID:ASI4
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ISSN:0002-8231
1097-4571
DOI:10.1002/(SICI)1097-4571(1999)50:5<413::AID-ASI4>3.0.CO;2-4