Applying genetic algorithms to query optimization in document retrieval

This paper proposes a novel approach to automatically retrieve keywords and then uses genetic algorithms to adapt the keyword weights. One of the contributions of the paper is to combine the Bigram (Chen, A., He, J., Xu, L., Gey, F. C., & Meggs, J. 1997. Chinese text retrieval without using a di...

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Bibliographic Details
Published in:	Information processing & management Vol. 36; no. 5; pp. 737 - 759
Main Authors:	Horng, Jorng-Tzong, Yeh, Ching-Chang
Format:	Journal Article
Language:	English
Published:	Oxford Elsevier Ltd 01.09.2000 Elsevier Science Elsevier Science Ltd
Subjects:	Algorithms Bigram Strategy Chinese Content analysis Exact sciences and technology Genetic algorithms Genetics Indexing. Classification. Abstracting. Syntheses Information and communication sciences Information and document structure and analysis Information processing and retrieval Information Retrieval Information science. Documentation Keyword Keywords Mathematical Formulas Online information retrieval Optimization PAT-tree Query Processing Relevance (Information Retrieval) Retrieval Sciences and techniques of general use Searching Studies Vector Spaces Weighted Term Searching Weighting Keyword Information retrieval PAT-tree Performance evaluation Automatic classification Weighting Genetic algorithm Automatic indexing Feedback regulation Cluster Method Comparative study Optimization
ISSN:	0306-4573, 1873-5371
Online Access:	Get full text
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