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Improving Retrieval Performance by Relevance Feedback

File(s)
88-898.pdf (1.57 MB)
88-898.ps (397.96 KB)
Permanent Link(s)
https://hdl.handle.net/1813/6738
Collections
Computer Science Technical Reports
Author
Salton, Gerard
Buckley, Chris
Abstract

Relevance feedback is an automatic process, introduced over 20 years ago, designed to produce query formulations following an initial retrieval operation. The principal relevance feedback methods described over the years are examined briefly, and evaluation data are included to demonstrate the effectiveness of the various methods. Prescriptions are given for conducting text retrieval operations iteratively using relevance feedback.

Date Issued
1988-02
Publisher
Cornell University
Keywords
computer science
•
technical report
Previously Published as
http://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.cs/TR88-898
Type
technical report

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