NDLI: Construction of High-quality Feature Extension Mode Library for Chinese Short-text Classification

Content Provider	IEEE Xplore Digital Library
Author	Xinghua Fan Hongge Hu
Copyright Year	2010
Abstract	One feasible way to handle the difficulties in the Chinese short-text classification is doing feature extension for its content. And a key technique of it is the construction of feature extension mode library whose quality would directly influence the effect of feature extension. This paper proposes a method of constructing a high-quality feature extension mode library. In our method, firstly, we obtained the feature extension modes from the training set, and then introduced three measures, i.e., confidence, category homoplasy and relevancy strength of the obtained feature extension mode, to improve their quality. Finally, we used the high-quality feature extension modes to construct a high-quality feature extension mode library. Experimental results show that (1) Introducing the three measures can improve the quality of feature extension mode in some degree respectively; (2)A high-quality feature extension mode library is helpful to improving the effect of Chinese short-text classification.
Starting Page	87
Ending Page	90
File Size	309216
Page Count	4
File Format	PDF
ISBN	9781424475063
e-ISBN	9781424475070
DOI	10.1109/ICIE.2010.117
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Chinese short-text classification high-quality feature extension mode library relevancy strength Text categorization Noise Finance confidence Lead Libraries Association rules category homoplasy
Content Type	Text
Resource Type	Article

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