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Text categorization, especially short text categorization, is a difficult and challenging task since the text data is sparse and multidimen-sional. In traditional text classification methods, document texts are repre-sented with ''Bag of Words (BOW)'' text representation schema, which is based on word co-occurrence and has many limitations. In this paper, we mapped document texts to Wikipedia concepts and used the Wikipedia-concept-based document representation method to take the place of tradi-tional BOW model for text classification. In order to overcome the weak-ness of ignoring the semantic relationships among terms in document rep-resentation model and utilize rich semantic knowledge in Wikipedia, we constructed a semantic matrix to enrich Wikipedia-concept-based docu-ment representation. Experimental evaluation on five real datasets of long and short text shows that our approach outperforms the traditional BOW method. © 2013 The Institute of Electronics, Information and Communication Engineers.

Improving Text Categorization with Semantic Knowledge in Wikipedia