Exploring Fuzzy Association Rules in Semantic Network Enrichment Improvement of the Semantic Indexing Process-Reference-Cited by-同舟云学术

Exploring Fuzzy Association Rules in Semantic Network Enrichment Improvement of the Semantic Indexing Process

Published:2018 Issue: Volume: Page:149-169
ISSN:2328-2762
Container-title:Innovations, Developments, and Applications of Semantic Web and Information Systems
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Author:

Mallat Souheyl¹,Hkiri Emna²,Zrigui Mounir¹

Affiliation:

1. Faculty of Science of Monastir, Tunisia

2. LATICE Laboratory, Tunisia

Abstract

In the aim of natural language processing applications improvement, we focus on statistical approach to semantic indexing for multilingual text documents based on conceptual network formalism. We propose to use this formalism as an indexing language to represent the descriptive concepts and their weighting. Our contribution is based on two steps. In the first step, we propose the extraction of index terms using the multilingual lexical resource EuroWordNet (EWN). In the second step, we pass from the representation of index terms to the representation of index concepts through conceptual network formalism. This network is generated using the EWN resource and pass by a classification step based on association rules modelOur proposed indexing approach can be applied to text documents in various languages. Next, we apply the same statistical process regardless of the language in order to extract the significant concepts and their associated weights. We prove that the proposed indexing approach provides encouraging results.

Publisher

IGI Global

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