Adaptive Linear Information Retrieval Models.
Peter Bollmann, S. K. Michael Wong:
Adaptive Linear Information Retrieval Models.
SIGIR 1987: 157-163@inproceedings{DBLP:conf/sigir/BollmannW87,
author = {Peter Bollmann and
S. K. Michael Wong},
title = {Adaptive Linear Information Retrieval Models},
booktitle = {Proceedings of the Tenth Annual International ACM SIGIR Conference
on Research and Development in Information Retrieval, New Orleans,
Louisiana, USA, June 3-5, 1987},
publisher = {ACM},
year = {1987},
pages = {157-163},
ee = {db/conf/sigir/BollmannW87.html},
crossref = {DBLP:conf/sigir/87},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX
Abstract
Linear decision (retrieval) functions have been widely adopted in information retrieval systems such as in Boolean, vector, and probabilistic models.
Based on measurement theory, adaptive linear retrieval models are proposed in this paper.
A necessary and sufficient condition for the existence of a linear decision function is given.
By ann inductive learning (feedback) process, techniques in linear integer programming can be directly applied to estimate parameters for automatic query formulation.
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BibTeX
Printed Edition
Proceedings of the Tenth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, New Orleans, Louisiana, USA, June 3-5, 1987.
ACM 1987
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