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
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