Title :
A Semantic Vector Retrieval Model for Desktop Documents
Author_Institution :
Sch. of Inf., Zhongnan Univ. of Economic & Law, Wuhan
Abstract :
The paper provides a semantic vector retrieval model for desktop documents based on the ontology. Comparing with traditional vector space model, the semantic model using semantic and ontology technology to solve several problems that traditional model could not overcome such as the shortcomings of weight computing based on statistical method, the expression of semantic relations between different keywords, the description of document semantic vectors and the similarity calculating, etc. Finally, the experimental results show that the retrieval ability of our new model has significant improvement both on recall and precision.
Keywords :
document handling; information retrieval; ontologies (artificial intelligence); desktop documents; document semantic vectors; ontologyontology technology; semantic vector retrieval model; similarity calculating; statistical method; weight computing; Computer science; Frequency; Information retrieval; Inverse problems; Ontologies; Semantic Web; Software engineering; Space technology; Statistical analysis; Technology management; information retrieval; ontology; samntic desktop; vector retrieval model;
Conference_Titel :
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-0-7695-3336-0
DOI :
10.1109/CSSE.2008.421