DocumentCode :
1909297
Title :
A Rough Concept Recognition Approach for Information Retrieval Based on Latent Semantic Analysis
Author :
Wang, Yi-chuan ; Guo, Yan-hui ; Li, Lei
Author_Institution :
Center for Intell. Sci. & Technol. Res., Beijing Univ. of Posts & Telecommun., Beijing
fYear :
2007
fDate :
Aug. 30 2007-Sept. 1 2007
Firstpage :
90
Lastpage :
95
Abstract :
This paper presents an information retrieval approach which uses a rough concept clustering in conjunction with Latent Semantic Analysis(LSA) to provide better document retrieval results matched to queries. The conceptual context defined in this article can be local, so no domain expert has to be involved in this approach. Our experiment consists of word clustering by similarity and rough concept recognition, associated to a basic LSA retrieval system. Our information retrieval process is illustrated through our experimentation model and results are compared in two different aspects. Experiment results show that retrieval performance benefit can be gained from this approach and further performance benefits can also be obtained according to the further work, which needs researching about parameter settings and algorithm development.
Keywords :
information retrieval; pattern clustering; word processing; information retrieval approach; latent semantic analysis; rough concept recognition approach; word clustering; Clustering algorithms; Clustering methods; Content based retrieval; Information analysis; Information retrieval; Matrix decomposition; Ontologies; Partitioning algorithms; Performance analysis; Target recognition; Concept Clustering Information Retrieval(IR); Latent Semantic Analysis(LSA);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Language Processing and Knowledge Engineering, 2007. NLP-KE 2007. International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-1610-3
Electronic_ISBN :
978-1-4244-1611-0
Type :
conf
DOI :
10.1109/NLPKE.2007.4368016
Filename :
4368016
Link To Document :
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