Please use this identifier to cite or link to this item: http://inaoe.repositorioinstitucional.mx/jspui/handle/1009/1618
Bilingual document clustering using Translation-Independent features
Claudia Denicia Carral
Manuel Montes y Gómez
Luis Villaseñor Pineda
RITA MARIANA ACEVES PEREZ
Acceso Abierto
Atribución-NoComercial-SinDerivadas
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.
IJCLA
2010
Artículo
Inglés
Estudiantes
Investigadores
Público en general
Denicia-Carral, C., et al., (2010). Bilingual document clustering using Translation-Independent features, IJCLA Vol. 1 (1-2): 217-230
CIENCIA DE LOS ORDENADORES
Versión aceptada
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Appears in Collections:Artículos de Ciencias Computacionales

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