How to Combine Text-Mining Methods to Validate Induced Verb-Object Relations? - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier Access content directly
Journal Articles Computer Science and Information Systems Year : 2014

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

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.
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Dates and versions

lirmm-01054918 , version 1 (09-08-2014)

Identifiers

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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, 2014, 11 (1), pp.133-155. ⟨10.2298/csis130528021b⟩. ⟨lirmm-01054918⟩
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