DocumentCode
2230431
Title
A Genetic System for Cluster Analysis for Hypertext Documents
Author
di Carlantonio, L.M. ; da Costa, R.M.E.
Author_Institution
Univ. do Estado do Rio de Janeiro - UERJ, Rio de Janeiro
fYear
2007
fDate
20-24 Oct. 2007
Firstpage
771
Lastpage
776
Abstract
Due to the increase in the number of WWW home pages, we are facing new challenges for information retrieval and indexing. Some "intelligent" techniques, including neural networks, symbolic learning, and genetic algorithms have been used to group different classes of data in an efficient way. This article describes a system for cluster analysis of hypertext documents based on genetic algorithms. The effectiveness of the system in getting groups with similar documents is evidenced by the experimental results.
Keywords
Internet; Web sites; genetic algorithms; hypermedia; information retrieval; neural nets; pattern clustering; statistical analysis; WWW home pages; cluster analysis; genetic algorithms; genetic system; hypertext documents; information retrieval; neural networks; symbolic learning; Algorithm design and analysis; Clustering algorithms; Data mining; Genetic algorithms; HTML; Information analysis; Intelligent systems; System analysis and design; Text analysis; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems Design and Applications, 2007. ISDA 2007. Seventh International Conference on
Conference_Location
Rio de Janeiro
Print_ISBN
978-0-7695-2976-9
Type
conf
DOI
10.1109/ISDA.2007.126
Filename
4389701
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