Semantic Network Formalism for Knowledge Representation
| Autor: | Emna Hkiri, Souheyl Mallat, Mounir Zrigui, Mohsen Maraoui |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Information retrieval
Probabilistic latent semantic analysis Knowledge representation and reasoning Computer Networks and Communications Computer science business.industry Semantic search Lexical database Semantic network Semantic similarity Semantic computing business EuroWordNet Information Systems |
| Zdroj: | International Journal on Semantic Web and Information Systems. 11:64-85 |
| ISSN: | 1552-6291 1552-6283 |
| DOI: | 10.4018/ijswis.2015100103 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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