A New Graph-Based Algorithm for Clustering Documents

Suárez, Airel Pérez; Trinidad, José Francisco Martínez; Carrasco-Ochoa, Jesús Ariel; Pagola, José E. Medina

doi:10.1109/icdmw.2008.69

Cited by 4 publications

(1 citation statement)

References 13 publications

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“…Second, the Direct algorithm has been previously used in BDC works (Montalvo et al 2006;, and the Star algorithm has been recently used in monolingual document clustering tasks (Sua ´rez et al 2008).…”

Section: Clustering Algorithmsmentioning

confidence: 99%

Bilingual Document Clustering: Evaluating Cognates as Features / Le groupage de documents bilingues : l’évaluation des cognats comme caractéristiques

Denicia-Carral¹,

Montes-y-Gómez²,

Villaseñor-Pineda³

et al. 2011

Canadian Journal of Information and Library Science

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This paper focuses on the task of bilingual clustering, which involves dividing a set of documents from two different languages into a set of groups, so that documents with similar topics belong to the same group, regardless of their source language. It mainly considers a clustering approach that relies on the use of cognates as document features. Particularly, it proposes two straightforward methods that extract cognates from their own target document collection and do not require using any external bilingual resource, like parallel corpora or a bilingual dictionary. Experimental results in two bilingual collections that include news reports in English and Spanish are encouraging. They indicate that cognates are relevant features for the task of bilingual clustering, outperforming by more than 10% the results achieved by other known approaches.

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Section: Clustering Algorithmsmentioning

confidence: 99%

Bilingual Document Clustering: Evaluating Cognates as Features / Le groupage de documents bilingues : l’évaluation des cognats comme caractéristiques

Denicia-Carral¹,

Montes-y-Gómez²,

Villaseñor-Pineda³

et al. 2011

Canadian Journal of Information and Library Science

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A New Incremental Algorithm for Overlapped Clustering

Suárez

Martínez-Trinidad

Carrasco-Ochoa

et al. 2009

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

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In this paper, a new algorithm for incremental overlapped clustering, called Incremental Clustering by Strength Decision (ICSD), is introduced. ICSD obtains a set of dense and overlapped clusters using a new graph cover heuristic while reduces the amount of computation by maintaining incrementally the cluster structure. The experimental results show that our proposal outperforms other graph-based clustering algorithms considering quality measures and also show that ICSD achieves a better time performance than other incremental graph-based algorithms.

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X-Cluster, A Novel and Efficient Approach towards Unsupervised Learning

Sharma

2013

2013 International Conference on Machine Intelligence and Research Advancement

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A New Graph-Based Algorithm for Clustering Documents

Cited by 4 publications

References 13 publications

Bilingual Document Clustering: Evaluating Cognates as Features / Le groupage de documents bilingues : l’évaluation des cognats comme caractéristiques

Bilingual Document Clustering: Evaluating Cognates as Features / Le groupage de documents bilingues : l’évaluation des cognats comme caractéristiques

A New Incremental Algorithm for Overlapped Clustering

X-Cluster, A Novel and Efficient Approach towards Unsupervised Learning

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