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Inhaltsverzeichnis
Referenz
M. Boughanem, C. Chrisment, L. Tamine: Genetic approach to query space exploration. Information Retrieval, 1 (1999), pp. 175–192
DOI
http://dx.doi.org/10.1023/A:1009931404333
Abstract
This paper describes a genetic algorithm approach for intelligent information retrieval. The goal is to find an optimal set of documents which best matches the user‘s needs by exploring and exploiting the document space. More precisely, we define a specific genetic algorithm for information retrieval based on knowledge based operators and guided by a heuristic for relevance multi-modality problem solving. Experiments with TREC-6 French data and queries show the effectiveness of our approach.
Extended Abstract
Bibtex
@article{Boughanem:1999:GAQ:593953.593970,
author = {Boughanem, M. and Chrisment, C. and Tamine, L.},
title = {Genetic Approach to Query Space Exploration},
journal = {Inf. Retr.},
issue_date = {October 1999},
volume = {1},
number = {3},
month = oct,
year = {1999},
issn = {1386-4564},
pages = {175--192},
numpages = {18},
url = {http://dx.doi.org/10.1023/A:1009931404333 http://de.evo-art.org/index.php?title=Genetic_approach_to_query_space_exploration},
doi = {10.1023/A:1009931404333},
acmid = {593970},
publisher = {Kluwer Academic Publishers},
address = {Hingham, MA, USA},
keywords = {genetic algorithm, information retrieval, relevance feedback},
}
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