DocumentCode
2124806
Title
A Concept-Relation Vector Model Based Method for Web Document Retrieval
Author
Liu, Yuan ; Zhanhuai, Li ; Longbo, Zhang ; Shiliang, Chen
Author_Institution
Sch. of Comput. Sci., Northwestern Poly Tech. Univ., Xian
fYear
2008
fDate
21-22 Dec. 2008
Firstpage
196
Lastpage
200
Abstract
Semantic information has been paid much attention in web IR. Although many researches have improved the retrieval performance by employing WordNet synset and concept, relations between concepts are often ignored by most of the semantic retrieval methods. We propose a relation enhanced concept vector model CRVM(concept-relation vector model) for document representation in this paper, and the documents to be retrieved are indexed by both concepts and relations. Domain ontology is employed to provide background knowledge for constructing concept based vector representation of documents. We prove the effectiveness of ontology concept and relation enhanced document representation for retrieving by web pages derived from WebKB data set and Open Directory Project.
Keywords
Internet; Web sites; document handling; information retrieval; ontologies (artificial intelligence); Open Directory Project; Web document retrieval; Web pages; WebKB data set; WordNet synset; concept-relation vector model based method; document representation; domain ontology; semantic retrieval methods; Computational efficiency; Computer science; Frequency; Information analysis; Information retrieval; Knowledge acquisition; Navigation; Ontologies; Semantic Web; Web pages; information retrieval; ontology; semantic retrieval;
fLanguage
English
Publisher
ieee
Conference_Titel
Knowledge Acquisition and Modeling, 2008. KAM '08. International Symposium on
Conference_Location
Wuhan
Print_ISBN
978-0-7695-3488-6
Type
conf
DOI
10.1109/KAM.2008.130
Filename
4732814
Link To Document