Authors:
Lamia Ben Ghezaiel
1
;
Chiraz Latiri
2
and
Mohamed Ben Ahmed
1
Affiliations:
1
Manouba University, Tunisia
;
2
El Manar University, Tunisia
Keyword(s):
Text Mining, Ontology Enrichment, Information Retrieval, Association Rule, Generic Basis, Distance Measures, Conceptual Indexing.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Data Engineering
;
Enterprise Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Acquisition
;
Knowledge Engineering and Ontology Development
;
Knowledge Representation
;
Knowledge-Based Systems
;
Ontologies and the Semantic Web
;
Ontology Engineering
;
Symbolic Systems
Abstract:
In this paper, we propose the use of a minimal generic basis of association rules (ARs) between terms, in order to automatically enrich an initial domain ontology. For this purpose, three distance measures are defined to link the candidate terms identified by ARs, to the initial concepts in the ontology. The final result is a proxemic conceptual network which contains additional implicit knowledge. Therefore, to evaluate our ontology enrichment approach, we propose a novel document indexing approach based on this proxemic network. The experiments carried out on the OHSUMED document collection of the TREC 9 filtring track and MeSH ontology showed that our conceptual indexing approach could considerably enhance information retrieval effectiveness.