NDLI: A binary classification method based on class space model

Content Provider	IEEE Xplore Digital Library
Author	Liu Tonglai Jiang Hua Wen Jing
Copyright Year	2010
Description	Author affiliation: School of Computer and Control, Guilin University of Electronic Technology, 541004, China (Liu Tonglai; Jiang Hua; Wen Jing)
Abstract	Aiming at the shortages that text classification depends on the vector space model and document frequency (DF) feature extraction method in binary classification in the recent time, a binary classification method based on difference frequency space model is proposed. This method breaks through the restriction of vector space model, extracts the features with improved methods of DF of difference frequency, and the function of the binary classification is implemented. Experimental results show that the improved method is effective. The precision, the Recall ratio and F1 test value in the classification results are all improved, the precision of the classification is also increased. In addition the method in this paper can be also used in the binary classification of other domains.
Starting Page	807
Ending Page	809
File Size	216091
Page Count	3
File Format	PDF
ISBN	9781424468348
e-ISBN	9781424468379
DOI	10.1109/ICISS.2010.5657095
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-22
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Difference frequency Helium Binary classification Text classification Class space model
Content Type	Text
Resource Type	Article

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