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Presenter : Cheng-Han Tsai Authors : Xiaojun Quan , Wenyin Liu, Senior Member, IEEE, and Bite Qiu TPAMI, 2012. Term Weighting Schemes for Question Categorization. Outlines. Motivation Objectives Methodology Experiments Conclusions Comments. Motivation. Text categorization.
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Presenter : Cheng-Han Tsai Authors : XiaojunQuan, Wenyin Liu, Senior Member, IEEE, and Bite Qiu TPAMI, 2012 Term Weighting Schemes for Question Categorization
Outlines Motivation Objectives Methodology Experiments Conclusions Comments
Motivation Text categorization Questions are usually a piece of short text, can the existing term-weighting methods perform consistently in question categorization as they do in text categorization?
Objectives UIQA This paper proposed new supervised term-weighting methods to deal with the problems that questions are usually a piece of short text
Methodology : :
Experiments – different values of k 20 Newsgroups Yahoo-natural Yahoo-500 Yahoo-1000
Experiments – different kernels Yahoo-500 Yahoo-1000
Experiments – different scales of data Yahoo-500 Yahoo-1000
Experiments – overall Statistical Significance Test10-fold cross-validation Value of k: 30 Kernel: LINEAR
Conclusions The three new methods, especially iqf*qf*icf, exhibit stable and consistent improvement over most of the previous term-weighting methods mentioned in the experiments.
Comments • Advantages • This paper compares to many well-known methods, and it performs well. • Applications • Question Categorization