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
Subjects
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
Information Resource
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
97