NESM: a Named Entity based Proximity Measure for Multilingual News Clustering

• Autores: X Soto Montalvo, Víctor Fresno Fernández , Raquel Martínez Lucas
• Localización: Procesamiento del lenguaje natural, ISSN 1135-5948, Nº. 48, 2012, págs. 81-88
• Idioma: inglés
• Títulos paralelos:
  • NESM: una medida de similitud para el clustering multilingüe de noticias basada en entidades nombradas
• Enlaces
  • Texto completo
• Resumen
  • español

    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.

  • English

    Measuring the similarity between documents is an essential task in Document Clustering. This paper presents a new metric that is based on the number and the category of the Named Entities shared between news documents. Three different feature-weighting functions and two standard similarity measures were used to evaluate the quality of the proposed measure in multilingual news clustering. The results, with three different collections of comparable news written in English and Spanish, indicate that the new metric performance is in some cases better than standard similarity measures such as cosine similarity and correlation coefficient.

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