Title

Bilingual document clustering using Translation-Independent features

Author

Claudia Denicia Carral

Manuel Montes y Gómez

Luis Villaseñor Pineda

RITA MARIANA ACEVES PEREZ

Access level

Open Access

Summary or description

This paper focuses on the task of bilingual clustering, which involves dividing a set of documents from two different languages into a set of thematically homogeneous groups. It mainly proposes a translation independent approach specially suited to deal with linguistically related languages. In particular, it proposes representing the documents by pairs of words orthographically or thematically related. The experimental evaluation in three bilingual collections and using two clustering algorithms demonstrated the appropriateness of the proposed representation, which results are comparable to those from other approaches based on complex linguistic resources such as translation machines, part-of-speech taggers, and named entity recognizers.

Publisher

IJCLA

Publish date

2010

Publication type

Article

Publication version

Accepted Version

Format

application/pdf

Language

English

Audience

Students

Researchers

General public

Citation suggestion

Denicia-Carral, C., et al., (2010). Bilingual document clustering using Translation-Independent features, IJCLA Vol. 1 (1-2): 217-230

Source repository

Repositorio Institucional del INAOE

Downloads

84

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