NESM: a Named Entity based Proximity Measure for Multilingual News Clustering
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| Formato: | Artículo científico |
| Lenguaje: | en |
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Sociedad Española para el Procesamiento del Lenguaje Natural
2012
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| _version_ | 1876486274808807424 |
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| author | Soto Montalvo |
| author_facet | Soto Montalvo |
| contents | NESM: a Named Entity based Proximity Measure for Multilingual News Clustering Soto Montalvo Víctor Fresno Raquel Martínez Computación Named entity document similarity multilingual clustering 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. 2012 artículo científico 1135-5948 https://www.redalyc.org/articulo.oa?id=515751748010 en http://www.redalyc.org/revista.oa?id=5157 Procesamiento del Lenguaje Natural application/pdf Sociedad Española para el Procesamiento del Lenguaje Natural Procesamiento del Lenguaje Natural (España) Num.48 |
| format | Artículo científico |
| id | redalyc_515751748010 |
| institution | Redalyc |
| language | en |
| publishDate | 2012 |
| publisher | Sociedad Española para el Procesamiento del Lenguaje Natural |
| spellingShingle | NESM: a Named Entity based Proximity Measure for Multilingual News Clustering Soto Montalvo Computación Named entity document similarity multilingual clustering NESM: a Named Entity based Proximity Measure for Multilingual News Clustering Soto Montalvo Víctor Fresno Raquel Martínez Computación Named entity document similarity multilingual clustering 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. 2012 artículo científico 1135-5948 https://www.redalyc.org/articulo.oa?id=515751748010 en http://www.redalyc.org/revista.oa?id=5157 Procesamiento del Lenguaje Natural application/pdf Sociedad Española para el Procesamiento del Lenguaje Natural Procesamiento del Lenguaje Natural (España) Num.48 |
| title | NESM: a Named Entity based Proximity Measure for Multilingual News Clustering |
| topic | Computación Named entity document similarity multilingual clustering |
| url | https://www.redalyc.org/articulo.oa?id=515751748010 |