DocumentCode
2119650
Title
The Method of Text Categorization on Imbalanced Datasets
Author
Xin-fu, Li ; Yan, Yu ; Peng, Yin
Author_Institution
Coll. of Math. & Comput. Sci., Hebei Univ., Baoding
fYear
2009
fDate
27-28 Feb. 2009
Firstpage
650
Lastpage
653
Abstract
In practical applications, datasets are usually imbalanced, but traditional approaches usually lead a low recognition rate. To address this problem, in this paper, over-sampling of the minority class has been proposed to increase the number of minority class, so as to achieve balance, thereby enhancing recognition rate of minority class. The experiments show that this approach achieved satisfactory results.
Keywords
classification; text analysis; imbalanced dataset; minority class recognition; text categorization; Application software; Artificial intelligence; Computer science; Educational institutions; Information retrieval; Machine learning; Mathematics; Seminars; Text categorization; Text recognition; SVM; TF-IDF; imbalanced dataset; text categorization;
fLanguage
English
Publisher
ieee
Conference_Titel
Communication Software and Networks, 2009. ICCSN '09. International Conference on
Conference_Location
Macau
Print_ISBN
978-0-7695-3522-7
Type
conf
DOI
10.1109/ICCSN.2009.70
Filename
5076934
Link To Document