Document clustering : Applications in a collaborative digital library
Identifieur interne : 001935 ( Main/Exploration ); précédent : 001934; suivant : 001936Document clustering : Applications in a collaborative digital library
Auteurs : Fuad Rahman [États-Unis] ; Aman Kumar [États-Unis] ; Yuilya Tamikova [États-Unis] ; Hassan Alam [États-Unis]Source :
- Proceedings of SPIE, the International Society for Optical Engineering [ 0277-786X ] ; 2006.
Descripteurs français
- Pascal (Inist)
English descriptors
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Abstract
This paper introduces a document clustering method within a commercial document repository, FileShare®. FileShare® is a commercial collaborative digital library offering facilities for sharing and accessing documents over a simple Internet browser (e.g. Microsoft® Internet Explorer®, Netscape® or Opera®) within groups of people working on common projects. As the number of documents increases within a digital library, displaying these documents in this environment poses a huge challenge. This paper proposes a document clustering method that uses a modified version of the traditional K-Means algorithm to categorize documents by their themes using lexical chaining within the FileShare® repository. The proposed algorithm is unsupervised, and has shown very high accuracy in a typical experimental setup.
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sort="Tamikova, Yuilya" uniqKey="Tamikova Y" first="Yuilya" last="Tamikova">Yuilya Tamikova</name><affiliation wicri:level="2"><inist:fA14 i1="01"><s1>Human Computer Interaction Group, BCL Technologies Inc., 990 Linden Drive, Suite #203</s1><s2>Santa Clara, CA 95050</s2><s3>USA</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ><sZ>4 aut.</sZ></inist:fA14><country>États-Unis</country><placeName><region type="state">Californie</region></placeName></affiliation></author><author><name sortKey="Alam, Hassan" sort="Alam, Hassan" uniqKey="Alam H" first="Hassan" last="Alam">Hassan Alam</name><affiliation wicri:level="2"><inist:fA14 i1="01"><s1>Human Computer Interaction Group, BCL Technologies Inc., 990 Linden Drive, Suite #203</s1><s2>Santa Clara, CA 95050</s2><s3>USA</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ><sZ>4 aut.</sZ></inist:fA14><country>États-Unis</country><placeName><region type="state">Californie</region></placeName></affiliation></author></analytic><series><title level="j" type="main">Proceedings of SPIE, the International Society for Optical Engineering</title><idno type="ISSN">0277-786X</idno><imprint><date when="2006">2006</date></imprint></series></biblStruct></sourceDesc><seriesStmt><title level="j" type="main">Proceedings of SPIE, the International Society for Optical Engineering</title><idno type="ISSN">0277-786X</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithm</term><term>Automatic classification</term><term>Electronic library</term><term>Experimental device</term><term>High precision</term><term>Internet</term><term>K means algorithm</term><term>Signal classification</term><term>Unsupervised classification</term></keywords><keywords scheme="Pascal" xml:lang="fr"><term>Algorithme</term><term>Classification automatique</term><term>Bibliothèque électronique</term><term>Internet</term><term>Algorithme k moyenne</term><term>Classification non supervisée</term><term>Précision élevée</term><term>Dispositif expérimental</term><term>Classification signal</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">This paper introduces a document clustering method within a commercial document repository, FileShare®. FileShare® is a commercial collaborative digital library offering facilities for sharing and accessing documents over a simple Internet browser (e.g. Microsoft® Internet Explorer®, Netscape® or Opera®) within groups of people working on common projects. As the number of documents increases within a digital library, displaying these documents in this environment poses a huge challenge. This paper proposes a document clustering method that uses a modified version of the traditional K-Means algorithm to categorize documents by their themes using lexical chaining within the FileShare® repository. The proposed algorithm is unsupervised, and has shown very high accuracy in a typical experimental setup.</div></front></TEI><affiliations><list><country><li>États-Unis</li></country><region><li>Californie</li></region></list><tree><country name="États-Unis"><region name="Californie"><name sortKey="Rahman, Fuad" sort="Rahman, Fuad" uniqKey="Rahman F" first="Fuad" last="Rahman">Fuad Rahman</name></region><name sortKey="Alam, Hassan" sort="Alam, Hassan" uniqKey="Alam H" first="Hassan" last="Alam">Hassan Alam</name><name sortKey="Kumar, Aman" sort="Kumar, Aman" uniqKey="Kumar A" first="Aman" last="Kumar">Aman Kumar</name><name sortKey="Tamikova, Yuilya" sort="Tamikova, Yuilya" uniqKey="Tamikova Y" first="Yuilya" last="Tamikova">Yuilya Tamikova</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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