How to Combine Text-Mining Methods to Validate Induced Verb-Object Relations?

Nicolas Béchet 1 Jacques Chauché 2 Violaine Prince 2 Mathieu Roche 3, 4, *
* Corresponding author
1 Equipe CODAG - Laboratoire GREYC - UMR6072
GREYC - Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen
2 TEXTE - Exploration et exploitation de données textuelles
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
3 ADVANSE - ADVanced Analytics for data SciencE
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
4 UMR TETIS - Territoires, Environnement, Télédétection et Information Spatiale
Abstract : 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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Journal articles
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-01054918
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Submitted on : Saturday, August 9, 2014 - 10:42:21 PM
Last modification on : Wednesday, September 18, 2019 - 4:04:04 PM
Long-term archiving on: Wednesday, November 26, 2014 - 4:55:59 PM

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CIRAD | AGROPARISTECH | CNRS | IRSTEA | GREYC | GREYC-CODAG | TEXTE | COMUE-NORMANDIE | ADVANSE | AGROPOLIS | LIRMM | MIPS | UNIV-MONTPELLIER | ENSICAEN | UNICAEN

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Nicolas Béchet, Jacques Chauché, Violaine Prince, Mathieu Roche. How to Combine Text-Mining Methods to Validate Induced Verb-Object Relations?. Computer Science and Information Systems, ComSIS Consortium, 2014, 11 (1), pp.133-155. ⟨10.2298/CSIS130528021B⟩. ⟨lirmm-01054918⟩

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