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A comparative study of TF*IDF, LSI and multi-words for text classification
Zhang, Wen1; Yoshida, Taketoshi2; Tang, Xijin3
2011-03-01
Source PublicationEXPERT SYSTEMS WITH APPLICATIONS
ISSN0957-4174
Volume38Issue:3Pages:2758-2765
AbstractOne of the main themes in text mining is text representation, which is fundamental and indispensable for text-based intellegent information processing. Generally, text representation inludes two tasks: indexing and weighting. This paper has comparatively studied TF*IDF, LSI and multi-word for text representation. We used a Chinese and an English document collection to respectively evaluate the three methods in information retreival and text categorization. Experimental results have demonstrated that in text categorization, LSI has better performance than other methods in both document collections. Also, LSI has produced the best performance in retrieving English documents. This outcome has shown that LSI has both favorable semantic and statistical quality and is different with the claim that LSI can not produce discriminative power for indexing. (C) 2010 Elsevier Ltd. All rights reserved.
KeywordText representation TF*IDF LSI Multi-word Text classification Information retrieval Text categorization
DOI10.1016/j.eswa.2010.08.066
Language英语
Funding ProjectNational Natural Science Foundation of China[90718042] ; National Natural Science Foundation of China[60873072] ; National Natural Science Foundation of China[60803023] ; National Hi-Tech RD Plan of China[2007AA010303] ; National Hi-Tech RD Plan of China[2007AA01Z179] ; National Basic Research Program[2007CB310802] ; Foundation of Young Doctors of Institute of Software, Chinese Academy of Sciences[ISCAS2009-DR03]
WOS Research AreaComputer Science ; Engineering ; Operations Research & Management Science
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Operations Research & Management Science
WOS IDWOS:000284863200158
PublisherPERGAMON-ELSEVIER SCIENCE LTD
Citation statistics
Cited Times:156[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/13040
Collection系统科学研究所
Affiliation1.Chinese Acad Sci, Inst Software, Lab Internet Software Technol, Beijing 100190, Peoples R China
2.Japan Adv Inst Sci & Technol, Sch Knowledge Sci, Nomi, Ishikawa 9231292, Japan
3.Chinese Acad Sci, Acad Math & Syst Sci, Inst Syst Sci, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Zhang, Wen,Yoshida, Taketoshi,Tang, Xijin. A comparative study of TF*IDF, LSI and multi-words for text classification[J]. EXPERT SYSTEMS WITH APPLICATIONS,2011,38(3):2758-2765.
APA Zhang, Wen,Yoshida, Taketoshi,&Tang, Xijin.(2011).A comparative study of TF*IDF, LSI and multi-words for text classification.EXPERT SYSTEMS WITH APPLICATIONS,38(3),2758-2765.
MLA Zhang, Wen,et al."A comparative study of TF*IDF, LSI and multi-words for text classification".EXPERT SYSTEMS WITH APPLICATIONS 38.3(2011):2758-2765.
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