A new label maximization based incremental neural clustering approach

Application to text clustering

Jean Charles Lamirel, RaghvenPhDa Mall, Shadi Al Shehabi, Ghada Safi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Neural clustering algorithms show high performance in the general context of the analysis of homogeneous textual dataset. This is especially true for the recent adaptive versions of these algorithms, like the incremental growing neural gas algorithm (IGNG) and the label maximization based incremental growing neural gas algorithm (IGNG-F). In this paper we highlight that there is a drastic decrease of performance of these algorithms, as well as the one of more classical algorithms, when a heterogeneous textual dataset is considered as an input. Specific quality measures and cluster labeling techniques that are independent of the clustering method are used for the precise performance evaluation. We provide variations to incremental growing neural gas algorithm exploiting in an incremental way knowledge from clusters about their current labeling along with cluster distance measure data. This solution leads to significant gain in performance for all types of datasets, especially for the clustering of complex heterogeneous textual data.

Original languageEnglish
Title of host publicationAdvances in Self-Organizing Maps - 8th International Workshop, WSOM 2011, Proceedings
Pages257-266
Number of pages10
DOIs
Publication statusPublished - 23 Jun 2011
Externally publishedYes
Event8th Workshop on Self-Organizing Maps, WSOM 2011 - Espoo, Finland
Duration: 13 Jun 201115 Jun 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6731 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other8th Workshop on Self-Organizing Maps, WSOM 2011
CountryFinland
CityEspoo
Period13/6/1115/6/11

Fingerprint

Text Clustering
Labels
Clustering
Labeling
Gases
Measure Data
Incremental Algorithm
Quality Measures
Distance Measure
Clustering Methods
Clustering Algorithm
Performance Evaluation
Clustering algorithms
High Performance
Decrease
Gas

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Lamirel, J. C., Mall, R., Al Shehabi, S., & Safi, G. (2011). A new label maximization based incremental neural clustering approach: Application to text clustering. In Advances in Self-Organizing Maps - 8th International Workshop, WSOM 2011, Proceedings (pp. 257-266). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6731 LNCS). https://doi.org/10.1007/978-3-642-21566-7_26

A new label maximization based incremental neural clustering approach : Application to text clustering. / Lamirel, Jean Charles; Mall, RaghvenPhDa; Al Shehabi, Shadi; Safi, Ghada.

Advances in Self-Organizing Maps - 8th International Workshop, WSOM 2011, Proceedings. 2011. p. 257-266 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6731 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Lamirel, JC, Mall, R, Al Shehabi, S & Safi, G 2011, A new label maximization based incremental neural clustering approach: Application to text clustering. in Advances in Self-Organizing Maps - 8th International Workshop, WSOM 2011, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6731 LNCS, pp. 257-266, 8th Workshop on Self-Organizing Maps, WSOM 2011, Espoo, Finland, 13/6/11. https://doi.org/10.1007/978-3-642-21566-7_26
Lamirel JC, Mall R, Al Shehabi S, Safi G. A new label maximization based incremental neural clustering approach: Application to text clustering. In Advances in Self-Organizing Maps - 8th International Workshop, WSOM 2011, Proceedings. 2011. p. 257-266. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-21566-7_26
Lamirel, Jean Charles ; Mall, RaghvenPhDa ; Al Shehabi, Shadi ; Safi, Ghada. / A new label maximization based incremental neural clustering approach : Application to text clustering. Advances in Self-Organizing Maps - 8th International Workshop, WSOM 2011, Proceedings. 2011. pp. 257-266 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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