DocumentCode :
2927744
Title :
Text Information Retrieval Based on Concept Semantic Similarity
Author :
Lv, Gang ; Zheng, Cheng ; Zhang, Li
Author_Institution :
Key Lab. of Network & Intell. Inf. Process., Hefei Univ., Hefei, China
fYear :
2009
fDate :
12-14 Oct. 2009
Firstpage :
356
Lastpage :
360
Abstract :
In this paper, an improved method of calculating ontology semantic similarity is proposed to enhance the information retrieval recall and precision. To filter out the document which have smaller related degree with original query, the scores of search results document is re-calculated by use of ontology semantic similarity. A new definition of the iterative query expansion parameters is put forward which can reduce the number of expansion and further improve the efficiency of the query. The use of open source tools for text semantic retrieval test, i.e., Jena and Lucene, has verified the feasibility and effectiveness of the proposed method.
Keywords :
information retrieval; iterative methods; ontologies (artificial intelligence); query processing; calculating ontology semantic; concept semantic similarity; further improve efficiency; iterative query expansion; search results document; text information retrieval; Computer networks; Context modeling; Grid computing; Information processing; Information retrieval; Intelligent networks; Laboratories; Ontologies; Signal processing; Solid modeling; Document Scores; Information Retrieval; Ontology; Query Expansion; Semantic Similarity;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Semantics, Knowledge and Grid, 2009. SKG 2009. Fifth International Conference on
Conference_Location :
Zhuhai
Print_ISBN :
978-0-7695-3810-5
Type :
conf
DOI :
10.1109/SKG.2009.18
Filename :
5370020
Link To Document :
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