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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| Published in: | Journal of the American Society for Information Science Vol. 50; no. 5; pp. 413 - 426 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
New York
John Wiley & Sons, Inc
1999
John Wiley & Sons |
| Subjects: | |
| 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. |
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| Bibliography: | ArticleID:ASI4 ark:/67375/WNG-TPQGPWXP-L istex:855066FA71AEDABDBA172D855D954DCB566B6AA7 ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 |
| ISSN: | 0002-8231 1097-4571 |
| DOI: | 10.1002/(SICI)1097-4571(1999)50:5<413::AID-ASI4>3.0.CO;2-4 |