DocumentCode
2823939
Title
Decision of Semantic Similarity Using Description Logic and Vector Weight between Concepts
Author
Kim, Su-Kyoung ; Choi, Ho-Jin
Author_Institution
Sch. of Eng., Inf. & Commun. Univ., Daejeon
Volume
2
fYear
2008
fDate
2-4 Sept. 2008
Firstpage
345
Lastpage
350
Abstract
Currently be proceeded a lot of researchers for ´user information demand description´ for interface of an information retrieval system or Web search engines, but user information demand description for a natural language form is a difficult situation. These reasons are as they cannot provide the semantic similarity that an information retrieval model can be completely satisfied with variety regarding an information demand expression and semantic relevance for user information description. Therefore, using the description logic which is a knowledge representation base of OWL and a vector model-based weight between concept, we proposes a method that can satisfy variety regarding an information demand expression, and proposes a decision method of semantic similarity for perfect assistances of user information demand description. The experiment results by proposed approach, semantic similarity of a polysemy and a synonym showed with excellent performance in decision.
Keywords
information retrieval; ontologies (artificial intelligence); search engines; semantic Web; OWL; Web search engines; description logic; information demand expression; information retrieval system; knowledge representation; natural language form; semantic similarity; user information demand description; vector model-based weight; vector weight; Computer interfaces; Computer networks; Information retrieval; Knowledge representation; Logic; Natural languages; OWL; Ontologies; Search engines; Web search;
fLanguage
English
Publisher
ieee
Conference_Titel
Networked Computing and Advanced Information Management, 2008. NCM '08. Fourth International Conference on
Conference_Location
Gyeongju
Print_ISBN
978-0-7695-3322-3
Type
conf
DOI
10.1109/NCM.2008.241
Filename
4624166
Link To Document