Semantic Network Formalism for Knowledge Representation: Towards Consideration of Contextual Information

In this paper, the authors propose formalism for representing a knowledge base (KB) by network. The objective is to achieve a high coverage of this base. This type of network is similar to the semantic network with the difference that the arcs are quantified by a value indicating the semantic proxim...

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Bibliographic Details
Published inInternational journal on semantic web and information systems Vol. 11; no. 4; pp. 64 - 85
Main Authors Mallat, Souheyl, Hkiri, Emna, Maraoui, Mohsen, Zrigui, Mounir
Format Journal Article
LanguageEnglish
Published Hershey IGI Global 01.10.2015
Subjects
Algorithms
Formalism
Information systems
Knowledge base
Knowledge bases (artificial intelligence)
Knowledge management
Knowledge representation
Networks
Proximity
Representations
Semantics
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Summary:In this paper, the authors propose formalism for representing a knowledge base (KB) by network. The objective is to achieve a high coverage of this base. This type of network is similar to the semantic network with the difference that the arcs are quantified by a value indicating the semantic proximity between the concepts. This semantic proximity presents taxonomic relations, synonyms, and non-taxonomic relations (contextual relations). This latter are discovered based on the association rules model. This model is based on (i) indexing method (ii) the French lexical database EuroWordNet (EWNF) and (iii) the Apriori algorithm. The contextual relations are the latent relations buried in the KB, carried by the semantic context. Evaluating our representation formalism shows better result about 80% of coverage of the KB.
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ISSN:1552-6283
1552-6291
DOI:10.4018/IJSWIS.2015100103