Name
Abstract | ||
|---|---|---|
In this paper, we propose a conceptual indexing documents approach based on an enriched ontology. We used a minimal generic basis of association rules (ARs) between terms, in order to automatically enrich an existing domain ontology. The final result is a proxemic conceptual network which contains additional implicit knowledge. Therefore, to evaluate our ontology enrichment approach, we propose a document indexing approach in IR 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. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.3233/978-1-61499-105-2-1920 | ADVANCES IN KNOWLEDGE-BASED AND INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS |
Keywords | Field | DocType |
Text mining,Ontology enrichment,Information retrieval,Association rule,Generic bases,Similarity measure,Conceptual Indexing | Ontology,Information retrieval,Conceptual indexing,Computer science | Conference |
Volume | ISSN | Citations |
243 | 0922-6389 | 1 |
PageRank | References | Authors |
0.37 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lamia Ben Ghezaiel | 1 | 3 | 1.80 |
| Cherif Chiraz Latiri | 2 | 18 | 7.96 |
| Mohamed Ben Ahmed | 3 | 195 | 45.34 |