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2009

Automatic Text Categorization of Mathematical Word Problems

8 years 6 months ago
Automatic Text Categorization of Mathematical Word Problems
This paper describes a novel application of text categorization for mathematical word problems, namely Multiplicative Compare and Equal Group problems. The empirical results and analysis show that common text processing techniques such as stopword removal and stemming should be selectively used. It is highly beneficial not to remove stopwords and not to do stemming. Part of speech tagging should also be used to distinguish words in discriminative parts of speech from the non-discriminative parts of speech which not only fail to help but even mislead the categorization decision for mathematical word problems. An SVM classifier with these selectively used text processing techniques outperforms an SVM classifier with a default setting of text processing techniques (i.e. stopword removal and stemming). Furthermore, a probabilistic meta classifier is proposed to combine the weighted results of two SVM classifiers with different word problem representations generated by different text prepr...
Suleyman Cetintas, Luo Si, Yan Ping Xin, Dake Zhan
Added 17 Feb 2011
Updated 17 Feb 2011
Type Journal
Year 2009
Where FLAIRS
Authors Suleyman Cetintas, Luo Si, Yan Ping Xin, Dake Zhang, Joo Young Park
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