Performance of Self-Taught Documents: Exploiting Co-Relevance Structure in a Document Collection.
Abraham Bookstein:
Performance of Self-Taught Documents: Exploiting Co-Relevance Structure in a Document Collection.
SIGIR 1986: 244-248@inproceedings{DBLP:conf/sigir/Bookstein86,
author = {Abraham Bookstein},
title = {Performance of Self-Taught Documents: Exploiting Co-Relevance
Structure in a Document Collection},
booktitle = {SIGIR'86, Proceedings of the 9th Annual International ACM SIGIR
Conference on Research and Development in Information Retrieval,
Pisa, Italy, September 8-10, 1986},
publisher = {ACM},
year = {1986},
pages = {244-248},
ee = {db/conf/sigir/Bookstein86.html},
crossref = {DBLP:conf/sigir/86},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX
Abstract
In this paper we study the behavior of an information retrieval system in which index terms are
assigned at random to both documents and requests. The random indexing is then modified by
means of a feedback mechanism derived from a normal probability model and applied to both the
request and document representations. Of interest is the convergence properties of the
representation vectors. After few feedback iterations, it is found that well defined clusters form that
accurately represent the corelevance structure among the documents--in effect the feedback
mechanism has permitted the documents to index themselves. This approach offers an interesting
way to extend the dimensionality of the indexing vocabulary. Both this application and a theoretical
analysis of the impact of extending the indexing vocabulary are discussed.
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BibTeX
Printed Edition
SIGIR'86, Proceedings of the 9th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Pisa, Italy, September 8-10, 1986.
ACM 1986
Contents BibTeX
Citation Page
Referenced by
- Clement T. Yu, Weiyi Meng, S. Park:
A Framework for Effective Retrieval.
ACM Trans. Database Syst. 14(2): 147-167(1989)
BibTeX
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