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

Carol Lundquist, Ophir Frieder, David O. Holmes and David Grossman

Journal of the American Society for Information Science, 1999, vol. 50, issue 5, 413-426

Abstract: 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.

Date: 1999
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https://doi.org/10.1002/(SICI)1097-4571(1999)50:53.0.CO;2-4

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Persistent link: https://EconPapers.repec.org/RePEc:bla:jamest:v:50:y:1999:i:5:p:413-426

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