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Probabilistic information retrieval based on conceptual overlap in semantic web ontologies (2004)
| Venue: | IN PROCEEDINGS OF THE 11TH FINNISH AI CONFERENCE, WEB INTELLIGENCE |
| Citations: | 9 - 0 self |
BibTeX
@INPROCEEDINGS{Holi04probabilisticinformation,
author = {Markus Holi and Eero Hyvönen},
title = {Probabilistic information retrieval based on conceptual overlap in semantic web ontologies},
booktitle = {IN PROCEEDINGS OF THE 11TH FINNISH AI CONFERENCE, WEB INTELLIGENCE},
year = {2004},
publisher = {}
}
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Abstract
Information retrieval systems have to deal with uncertain knowledge and query results should reflect this uncertainty in some manner. However, Semantic Web ontologies are based on crisp logic and do not provide well-defined means for expressing uncertainty. We present a new probabilistic method to approach the problem. In our method, degrees of subsumption, i.e., overlap between concepts can be modeled and computed efficiently using Bayesian networks based on RDF(S) ontologies. Degrees of overlap indicate how well an individual data item matches the query concept, which can be used as a well-defined measure of relevance in information retrieval tasks.
Keyphrases
semantic web ontology probabilistic information retrieval conceptual overlap bayesian network well-defined measure information retrieval system new probabilistic method query concept well-defined mean information retrieval task individual data item uncertain knowledge query result crisp logic
