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