InforLorV4, Main, Exploration, bibRecord, 002736

Comparative Behaviour of Recent Incremental and Non-incremental Clustering Methods on Text: An Extended Study

Identifieur interne : 002736 ( Main/Exploration ); précédent : 002735; suivant : 002737

Comparative Behaviour of Recent Incremental and Non-incremental Clustering Methods on Text: An Extended Study

Auteurs : Jean-Charles Lamirel [France] ; Raghvendra Mall [Inde] ; Mumtaz Ahmad [France]

Source :

Lecture Notes in Computer Science [ 0302-9743 ]

RBID : ISTEX:6A5356072F6EB6B6173A6EC0874B6D12CC0BF1A3

Abstract

Abstract: This paper represents an attempt to throw some light on the quality and on the defects of some recent clustering methods, either they are incremental or not, on “real world data”. An extended evaluation of the methods is achieved through the use of textual datasets of increasing complexity. The third test dataset is a highly polythematic dataset that figures out a static simulation of evolving data. It thus represents an interesting benchmark for comparing the behaviour of incremental and non incremental methods. The focus is put on neural clustering methods but the standard K-means method is included as reference in the comparison. Generic quality measures are used for quality evaluation.

Url:

https://api.istex.fr/ark:/67375/HCB-JT6TSTW2-X/fulltext.pdf

DOI: 10.1007/978-3-642-21822-4_3

Affiliations:

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to stream Istex, to step Corpus: 001880
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to stream Main, to step Curation: 002736

Le document en format XML

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Comparative Behaviour of Recent Incremental and Non-incremental Clustering Methods on Text: An Extended Study

Comparative Behaviour of Recent Incremental and Non-incremental Clustering Methods on Text: An Extended Study

Source :

Abstract

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