DocumentCode :
3022971
Title :
Research on Ontology-Based Case Indexing in CBR
Author :
Wang, Dong ; Xiang, Yang ; Zou, Guobing ; Zhang, Bo
Author_Institution :
Coll. of Electron. & Inf. Eng., Tongji Univ., Shanghai, China
Volume :
4
fYear :
2009
fDate :
7-8 Nov. 2009
Firstpage :
238
Lastpage :
241
Abstract :
This paper presents methods that support case retrieval in case-based reasoning system. We used the ontology to describe the relationship between terms in application fields. The similar cases are retrieval by calculating semantic similarity which we have defined. We evaluated traditional method of calculating the semantic similarity with lattice theory. We have constructed a decision support CBR prototype system of marketing strategy, based on this algorithm, which contains more than 600 cases. The evaluation shows that with the support of semantic, we can not only carry out data matching retrieval, but also perform semantic associated data access. CBR can quickly and accurately retrieve cases and improve efficiency of reasoning by semantic query.
Keywords :
case-based reasoning; indexing; ontologies (artificial intelligence); query processing; case indexing; case retrieval; case-based reasoning; data matching retrieval; decision support CBR; lattice theory; marketing strategy; ontology; semantic associated data access; semantic query; semantic similarity; Artificial intelligence; Computational intelligence; Consumer electronics; Educational institutions; Indexing; Information retrieval; Lattices; Ontologies; Prototypes; Vocabulary; Case Based Reasonin; Case retrieval; Ontolog; Semantics similarity;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3835-8
Electronic_ISBN :
978-0-7695-3816-7
Type :
conf
DOI :
10.1109/AICI.2009.449
Filename :
5376370
Link To Document :
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