Title :
Retrieving and Ranking Methods for Finding Match Candidates
Author :
Kim, Jung-Min ; Chung, Hyun-Sook
Author_Institution :
Dept. of Comput. Eng., Daejin Univ., Pocheon, South Korea
fDate :
June 30 2011-July 2 2011
Abstract :
Until now, many ontology matching approaches that are applicable to topic maps have been proposed. However, they assume that two ontologies are given before matching and they do not consider searching and selecting the most appropriate ontology from ontology libraries. In our system, topic maps can be searched by a topic map, which is entered by user in order to be evolved by matching and merging with the most appropriate topic map from available topic maps collection. To provide the best search result to user, we develop a ranking method based on syntactic and semantic structure of topics.
Keywords :
information retrieval; ontologies (artificial intelligence); match candidates; ontology matching approach; ranking methods; retrieving methods; topic maps; Density measurement; Merging; OWL; Ontologies; Resource description framework; Semantics; Ontology Search; Topic Maps Matching; Topic Maps Ranking; Topic Maps Search;
Conference_Titel :
Complex, Intelligent and Software Intensive Systems (CISIS), 2011 International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-61284-709-2
Electronic_ISBN :
978-0-7695-4373-4
DOI :
10.1109/CISIS.2011.36