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How to Combine Text-Mining Methods to Validate Induced Verb-Object Relations
Computer Science and Information Systems, Tome 11 (2014) no. 1
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This paper describes methods using Natural Language Processing approaches to extract and validate induced syntactic relations (here restricted to the Verb-Object relation). These methods use a syntactic parser and a semantic closeness measure to extract such relations. Then, their validation is based on two different techniques: A Web Validation system on one part, then a Semantic-Vectorbased approach, and finally different combinations of both techniques in order to rank induced Verb-Object relations. The Semantic Vector approach is a Roget-based method which computes a syntactic relation as a vector. Web Validation uses a search engine to determine the relevance of a syntactic relation according to its popularity. An experimental protocol is set up to judge automatically the relevance of the sorted induced relations. We finally apply our approach on a French corpus of news by using ROC Curves to evaluate the results.
Keywords: Text-Mining, Web-Mining, Syntactic Analysis 
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     author = {Nicolas Bechet and Jacques Chauche and Violaine Prince and Mathieu Roche},
     title = {How to {Combine} {Text-Mining} {Methods} to {Validate} {Induced} {Verb-Object} {Relations}},
     journal = {Computer Science and Information Systems},
     year = {2014},
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     url = {http://geodesic.mathdoc.fr/item/CSIS_2014_11_1_a10/}
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Nicolas Bechet; Jacques Chauche; Violaine Prince; Mathieu Roche. How to Combine Text-Mining Methods to Validate Induced Verb-Object Relations. Computer Science and Information Systems, Tome 11 (2014) no. 1. http://geodesic.mathdoc.fr/item/CSIS_2014_11_1_a10/