Multilingual Evaluation of KnowNet
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| Format: | Artículo científico |
| Sprache: | en |
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Sociedad Española para el Procesamiento del Lenguaje Natural
2008
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| _version_ | 1876488906933796864 |
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| author | Montse Cuadros |
| author_facet | Montse Cuadros |
| contents | Multilingual Evaluation of KnowNet Montse Cuadros German Rigau Computación Large Knowledge Acquisition Scale Knowledge Resources Word Sense Disambiguation This paper presents a new fully automatic method for building highly dense and accurate knowledge bases from existing semantic resources. Basically, the method uses a wide-coverage and accurate knowledge-based Word Sense Dis- ambiguation algorithm to assign the most appropriate senses to large sets of topi- cally related words acquired from the web. KnowNet, the resulting knowledge-base which connects large sets of semantically-related concepts is a major step towards the autonomous acquisition of knowledge from raw corpora. In fact, KnowNet is several times larger than any available knowledge resource encoding relations be- tween synsets, and the knowledge KnowNet contains outperform any other resource when is empirically evaluated in a common multilingual framework. 2008 artículo científico 1135-5948 https://www.redalyc.org/articulo.oa?id=515751741015 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.41 |
| format | Artículo científico |
| id | redalyc_515751741015 |
| institution | Redalyc |
| language | en |
| publishDate | 2008 |
| publisher | Sociedad Española para el Procesamiento del Lenguaje Natural |
| spellingShingle | Multilingual Evaluation of KnowNet Montse Cuadros Computación Large Knowledge Acquisition Scale Knowledge Resources Word Sense Disambiguation Multilingual Evaluation of KnowNet Montse Cuadros German Rigau Computación Large Knowledge Acquisition Scale Knowledge Resources Word Sense Disambiguation This paper presents a new fully automatic method for building highly dense and accurate knowledge bases from existing semantic resources. Basically, the method uses a wide-coverage and accurate knowledge-based Word Sense Dis- ambiguation algorithm to assign the most appropriate senses to large sets of topi- cally related words acquired from the web. KnowNet, the resulting knowledge-base which connects large sets of semantically-related concepts is a major step towards the autonomous acquisition of knowledge from raw corpora. In fact, KnowNet is several times larger than any available knowledge resource encoding relations be- tween synsets, and the knowledge KnowNet contains outperform any other resource when is empirically evaluated in a common multilingual framework. 2008 artículo científico 1135-5948 https://www.redalyc.org/articulo.oa?id=515751741015 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.41 |
| title | Multilingual Evaluation of KnowNet |
| topic | Computación Large Knowledge Acquisition Scale Knowledge Resources Word Sense Disambiguation |
| url | https://www.redalyc.org/articulo.oa?id=515751741015 |