Skip to Main content Skip to Navigation
Conference papers

Matching Fusion with Conceptual Indexing

Abstract : Many studies have been addressed the term-mismatch problem, which arises when using different terms or words for expressing the same meaning. We also introduce another problem: over-specialized document, which is caused when IR systems prefer documents that have poor query-document intersection, but with high weighting value, to those that have rich query-document intersection with low weighting value. In this study, we propose to use, simultaneously, multiple types of indexing elements: ngrams, keywords, and concepts, instead of only keywords. We followed a late data-fusion technique to achieve that. Through our proposed model, we also try to overcome the over-specialized document problem. Experiments for model validation have been done by using ImageCLEF2011 test collection, UMLS2009 Meta-thesaurus, and MetaMap tool for mapping text into UMLS concepts.
Document type :
Conference papers
Complete list of metadatas

Cited literature [32 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-00770561
Contributor : Valérie Samper <>
Submitted on : Monday, January 7, 2013 - 10:29:19 AM
Last modification on : Friday, July 17, 2020 - 11:10:27 AM
Long-term archiving on: : Monday, April 8, 2013 - 11:12:54 AM

File

Abdulahhad-Chevallet-Berrut_RI...
Files produced by the author(s)

Identifiers

  • HAL Id : hal-00770561, version 1

Collections

Citation

Karam Abdulahhad, Jean-Pierre Chevallet, Catherine Berrut. Matching Fusion with Conceptual Indexing. RISE 2012 - Atelier Recherche d'Information SEmantique (associé à la conférence EGC 2012), Jan 2012, Bordeaux, France. pp.34-45. ⟨hal-00770561⟩

Share

Metrics

Record views

532

Files downloads

133