Name
Abstract | ||
|---|---|---|
Information retrieval remains problematic in spite of the numerous existing search engines. It is the same problem for health information retrieval. We propose in this paper to combine three knowledge-based methods to enhance information retrieval using query expansion in the context of the CISMeF project (Catalogue and Index of French-speaking Medical Sites) in which the resources are indexed according to a structured terminology of the medical domain and a set of metadata. The first method consists of building and using morphological knowledge of the terms. The second method consists of extracting association rules between terms by applying a data mining technique over the indexed resources. The last method consists of formalizing the terminology using the OWL-DL language to benefit from its powerful reasoning mechanisms. We describe how these methods could be used conjointly in the KnowQuE prototype (Knowledge-based Query Expansion) and we give some preliminary results. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1007/978-3-540-25957-2_20 | LECTURE NOTES IN COMPUTER SCIENCE |
Keywords | Field | DocType |
terminology,data analysis,information retrieval,data mining,metadata,health,association rule,search engine,statistical association,knowledge base,indexation,information extraction,query expansion,artificial intelligence | Data mining,Metadata,Search engine,Information retrieval,Terminology,Query expansion,Computer science,Association rule learning,Information extraction,Health information retrieval,Knowledge base | Conference |
Volume | ISSN | Citations |
3055 | 0302-9743 | 4 |
PageRank | References | Authors |
0.52 | 10 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lina Fatima Soualmia | 1 | 98 | 20.27 |
| Stéfan Jacques Darmoni | 2 | 260 | 52.57 |