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...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Information processing & management Ročník 36; číslo 5; s. 737 - 759
Hlavní autoři:	Horng, Jorng-Tzong, Yeh, Ching-Chang
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Oxford Elsevier Ltd 01.09.2000 Elsevier Science Elsevier Science Ltd
Témata:	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
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!