How to combine text-mining methods to validate induced verb-object relations
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.
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dig-cirad-fr-5723562022-03-30T15:03:11Z http://agritrop.cirad.fr/572356/ http://agritrop.cirad.fr/572356/ How to combine text-mining methods to validate induced verb-object relations. Béchet Nicolas, Chauche Jacques, Prince Violaine, Roche Mathieu. 2014. Computer Science and Information Systems, 11 (1) : 133-156.https://doi.org/10.2298/CSIS130528021B <https://doi.org/10.2298/CSIS130528021B> Researchers How to combine text-mining methods to validate induced verb-object relations Béchet, Nicolas Chauche, Jacques Prince, Violaine Roche, Mathieu eng 2014 Computer Science and Information Systems C30 - Documentation et information 000 - Autres thèmes U30 - Méthodes de recherche 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. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/572356/1/document_572356.pdf application/pdf Cirad license info:eu-repo/semantics/openAccess https://agritrop.cirad.fr/mention_legale.html https://doi.org/10.2298/CSIS130528021B 10.2298/CSIS130528021B info:eu-repo/semantics/altIdentifier/doi/10.2298/CSIS130528021B info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.2298/CSIS130528021B |
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C30 - Documentation et information 000 - Autres thèmes U30 - Méthodes de recherche C30 - Documentation et information 000 - Autres thèmes U30 - Méthodes de recherche Béchet, Nicolas Chauche, Jacques Prince, Violaine Roche, Mathieu How to combine text-mining methods to validate induced verb-object relations |
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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. |
format |
article |
topic_facet |
C30 - Documentation et information 000 - Autres thèmes U30 - Méthodes de recherche |
author |
Béchet, Nicolas Chauche, Jacques Prince, Violaine Roche, Mathieu |
author_facet |
Béchet, Nicolas Chauche, Jacques Prince, Violaine Roche, Mathieu |
author_sort |
Béchet, Nicolas |
title |
How to combine text-mining methods to validate induced verb-object relations |
title_short |
How to combine text-mining methods to validate induced verb-object relations |
title_full |
How to combine text-mining methods to validate induced verb-object relations |
title_fullStr |
How to combine text-mining methods to validate induced verb-object relations |
title_full_unstemmed |
How to combine text-mining methods to validate induced verb-object relations |
title_sort |
how to combine text-mining methods to validate induced verb-object relations |
url |
http://agritrop.cirad.fr/572356/ http://agritrop.cirad.fr/572356/1/document_572356.pdf |
work_keys_str_mv |
AT bechetnicolas howtocombinetextminingmethodstovalidateinducedverbobjectrelations AT chauchejacques howtocombinetextminingmethodstovalidateinducedverbobjectrelations AT princeviolaine howtocombinetextminingmethodstovalidateinducedverbobjectrelations AT rochemathieu howtocombinetextminingmethodstovalidateinducedverbobjectrelations |
_version_ |
1758024070587219968 |