Improving retrieval performance by relevance feedback
G. Salton, and C. Buckley. Journal of the American Society for Information Science, (1990)
Abstract
Relevance feedback is an automatic process, introduced over 20 years ago, designed to produce improved 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 re-trieval operations iteratively using relevance feedback. Introduction to Relevance Feedback It is well known that the original query formulation process is not transparent to most information system users. In particular, without detailed knowledge of the collection make-up, and of the retrieval environment, most users find
Description
Improving retrieval performance by relevance feedback
%0 Journal Article
%1 Salton1990
%A Salton, Gerard
%A Buckley, Chris
%D 1990
%J Journal of the American Society for Information Science
%K classic idf information ir retrieval
%P 288--297
%T Improving retrieval performance by relevance feedback
%U http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.92.3553
%V 41
%X Relevance feedback is an automatic process, introduced over 20 years ago, designed to produce improved 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 re-trieval operations iteratively using relevance feedback. Introduction to Relevance Feedback It is well known that the original query formulation process is not transparent to most information system users. In particular, without detailed knowledge of the collection make-up, and of the retrieval environment, most users find
@article{Salton1990,
abstract = {Relevance feedback is an automatic process, introduced over 20 years ago, designed to produce improved 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 re-trieval operations iteratively using relevance feedback. Introduction to Relevance Feedback It is well known that the original query formulation process is not transparent to most information system users. In particular, without detailed knowledge of the collection make-up, and of the retrieval environment, most users find},
added-at = {2011-09-13T22:09:54.000+0200},
author = {Salton, Gerard and Buckley, Chris},
biburl = {https://www.bibsonomy.org/bibtex/296ff941f83c203fec17656805566a93e/jil},
description = {Improving retrieval performance by relevance feedback},
interhash = {8e637ba4c34ab1f529a12b18b5d52e24},
intrahash = {96ff941f83c203fec17656805566a93e},
journal = {Journal of the American Society for Information Science},
keywords = {classic idf information ir retrieval},
pages = {288--297},
timestamp = {2013-11-23T20:11:51.000+0100},
title = {Improving retrieval performance by relevance feedback},
url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.92.3553},
volume = 41,
year = 1990
}