DocumentCode
673003
Title
Short Text Classification Using Wikipedia Concept Based Document Representation
Author
Xiang Wang ; Ruhua Chen ; Yan Jia ; Bin Zhou
Author_Institution
Sch. of Comput., Nat. Univ. of Defense Technol., Changsha, China
fYear
2013
fDate
16-17 Nov. 2013
Firstpage
471
Lastpage
474
Abstract
Short text classification is a difficult and challenging task in information retrieval systems since the text data is short, sparse and multidimensional. In this paper, we represent short text with Wikipedia concepts for classification. Short document text is mapped to Wikipedia concepts and the concepts are then used to represent document for text categorization. Traditional methods for classification such as SVM can be used to perform text categorization on the Wikipedia concept document representation. Experimental evaluation on real Google search snippets shows that our approach outperforms the traditional BOW method and gives good performance. Although it´s not better than the state-of-the-art classifier (see e.g. Phan et al. WWW ´08), our method can be easily implemented with low cost.
Keywords
Web sites; information retrieval; pattern classification; text analysis; Google search snippets; SVM; information retrieval systems; multidimensional text data; short document text data mapping; short text classification; sparse text data; text categorization; wikipedia concept document representation; Electronic publishing; Encyclopedias; Indexes; Internet; Support vector machines; Text categorization; Document Representation; Short Text Classification; Wikipedia;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Technology and Applications (ITA), 2013 International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4799-2876-7
Type
conf
DOI
10.1109/ITA.2013.114
Filename
6710030
Link To Document