ACM SIGMOD Anthology SIGIR dblp.uni-trier.de

An Application of Least Squares Fit Mapping to Text Information Retrieval.

Yiming Yang, Christopher G. Chute: An Application of Least Squares Fit Mapping to Text Information Retrieval. SIGIR 1993: 281-290
@inproceedings{DBLP:conf/sigir/YangC93,
  author    = {Yiming Yang and
               Christopher G. Chute},
  editor    = {Robert Korfhage and
               Edie M. Rasmussen and
               Peter Willett 0002},
  title     = {An Application of Least Squares Fit Mapping to Text Information
               Retrieval},
  booktitle = {Proceedings of the 16th Annual International ACM-SIGIR Conference
               on Research and Development in Information Retrieval. Pittsburgh,
               PA, USA, June 27 - July 1, 1993},
  publisher = {ACM},
  year      = {1993},
  isbn      = {0-89791-605-0},
  pages     = {281-290},
  ee        = {db/conf/sigir/YangC93.html},
  crossref  = {DBLP:conf/sigir/93},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX

Abstract

This paper describes a unique example-based mapping method for document retrieval. We discovered that the knowledge about relevance among queries and documents can be used to obtain empirical connections between query terms and the canonical concepts which are used for indexing the content of documents. These connections do not depend on whether there are shared terms among the queries and documents; therefore, they are especially effective for a mapping from queries to the documents where the concepts are relevant but the terms used by article authors happen to be different from the terms of database users. We employ a Linear Least Squares Fit (LLSF) technique to compute such connections from a collection of queries and documents where the relevance is assigned by humans, and then use these connections in the retrieval of documents where the relevance is unknown. We tested this method on both retrieval and indexing with a set of MEDLINE documents which has been used by other information retrieval systems for evaluations. The effectiveness of the LLSF mapping and the significant improvement over alternative approaches was evident in the tests.

Copyright © 1993 by the ACM, Inc., used by permission. Permission to make digital or hard copies is granted provided that copies are not made or distributed for profit or direct commercial advantage, and that copies show this notice on the first page or initial screen of a display along with the full citation.


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Robert Korfhage, Edie M. Rasmussen, Peter Willett (Eds.): Proceedings of the 16th Annual International ACM-SIGIR Conference on Research and Development in Information Retrieval. Pittsburgh, PA, USA, June 27 - July 1, 1993. ACM 1993, ISBN 0-89791-605-0
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