DDOC: Overlapping Clustering of Words for Document Classification

DDOC: Overlapping Clustering of Words for Document Classification

In this paper we study the interest of integration of an overlapping clustering approach rather than traditional hard-clustering ones, in the context of dimensionality reduction of the description space for document classification. The Distributional Divisive Overlapping Clustering (DDOC) method is...

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Veröffentlicht in:Lecture notes in computer science 2004, p.127-128
Hauptverfasser: Cleuziou, Guillaume, Martin, Lionel, Clavier, Viviane, Vrain, Christel
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Sprache:eng
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Applied sciences
Computer science
control theory
systems
Data processing. List processing. Character string processing
Exact sciences and technology
Memory organisation. Data processing
Software
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Martin, Lionel
Clavier, Viviane
Vrain, Christel
description In this paper we study the interest of integration of an overlapping clustering approach rather than traditional hard-clustering ones, in the context of dimensionality reduction of the description space for document classification. The Distributional Divisive Overlapping Clustering (DDOC) method is briefly presented and compared to Agglomerative Distributional Clustering (ADC) [2] and Information-Theoretical Divisive Clustering (ITDC) [3] on the two corpus Reuters-21578 and 20Newsgroup.
doi_str_mv 10.1007/978-3-540-30213-1_17
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subjects Applied sciences
Computer science
control theory
systems
Data processing. List processing. Character string processing
Exact sciences and technology
Memory organisation. Data processing
Software
title DDOC: Overlapping Clustering of Words for Document Classification
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