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Question classification for e-learning by artificial neural network

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4 Author(s)
Ting Fei ; Nat. Univ. of Singapore, Singapore ; Wei Jyh Heng ; Kim Chuan Toh ; Tian Qi

Text categorization is the classification of unstructured text documents with respect to a set of one or more predefined categories. This paper describes our work in exploring automatic question classification tests which can be used in e-learning system. Such tests can take the form of multiple-choice tests, as well as fill-in-the-blank and short-answer tests. We acquired 20 texts used for high school students and each text is followed by several multiple choice questions from e-learning Webpage. We propose a text categorization model using an artificial neural network trained by the backpropagation learning algorithm as the text classifier. Our test results show that the system achieved the performance in terms of F1 value of nearly 78%.

Published in:

Information, Communications and Signal Processing, 2003 and Fourth Pacific Rim Conference on Multimedia. Proceedings of the 2003 Joint Conference of the Fourth International Conference on  (Volume:3 )

Date of Conference:

15-18 Dec. 2003

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