How to combine text-mining methods to validate induced verb-object relations

Béchet Nicolas, Chauche Jacques, Prince Violaine, Roche Mathieu. 2014. How to combine text-mining methods to validate induced verb-object relations. Computer Science and Information Systems, 11 (1) : 133-156.

Quartile : Q4, Sujet : COMPUTER SCIENCE, SOFTWARE ENGINEERING / Quartile : Q4, Sujet : COMPUTER SCIENCE, INFORMATION SYSTEMS

Résumé : 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.

Classification Agris : C30 - Documentation et information
000 - Autres thèmes
U30 - Méthodes de recherche

Champ stratégique Cirad : Hors axes (2014-2018)

Auteurs et affiliations

• Béchet Nicolas, Université de Caen (FRA)
• Chauche Jacques, LIRMM (FRA)
• Prince Violaine, LIRMM (FRA)
• Roche Mathieu, CIRAD-ES-UMR TETIS (FRA) ORCID: 0000-0003-3272-8568

Source : Cirad - Agritrop (https://agritrop.cirad.fr/572356/)

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