Innovative Term-Weighting Methods for Question Categorization
This research paper introduces new term-weighting methods for question categorization, addressing challenges posed by short text questions. The study includes detailed methodology, experiments on various datasets, and concludes with significant improvements over existing methods.
Innovative Term-Weighting Methods for Question Categorization
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Presentation Transcript
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
