NESMa Named Entity based Proximity Measure for Multilingual News Clustering

  1. Soto Montalvo, X
  2. Fresno Fernández, Víctor
  3. Martínez Lucas, Raquel
Revista:
Procesamiento del lenguaje natural

ISSN: 1135-5948

Any de publicació: 2012

Número: 48

Pàgines: 81-88

Tipus: Article

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Altres publicacions en: Procesamiento del lenguaje natural

Resum

Una de las tareas esenciales dentro del proceso del Clustering de Documentos es medir la similitud entre éstos. En este trabajo se presenta una nueva medida basada en el número y la categoría de las Entidades Nombradas compartidas entre documentos. Para evaluar la calidad de la medida propuesta en el clustering multilingüe de noticias, se han utilizado tres medidas de pesado diferentes y dos medidas de similitud estándar. Los resultados demuestran, con tres colecciones de noticias comparables escritas en español e inglés, que la medida propuesta es competitiva, superando en algunos casos a medidas como el coseno y el coeficiente de correlación.

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