Chua, Stephanie and Coenen, Frans (2013) An inductive rule learning technique for next mining in questionnaires. In: 4th International Conference on Computing and Informatics (ICOCI 2013), 28 -30 August 2013, Kuching, Sarawak, Malaysia.

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Abstract

This paper describes an inductive rule learning (IRL) technique for classifying questionnaires based on the natural language responses to the open-ended questions frequently found in questionnaire data.These responses are deemed to provide important information to the purpose of the questionnaire.Given that the responses are in the form of unstructured natural language text and that a collection of questionnaires can comprise thousands of returns, an automated approach for handling such text is desirable for analysis purposes.One common analysis task is the classification of questionnaires.For this purpose, an IRL technique is presented.An empirical comparison is also conducted to compare the presented technique with other established machine learning techniques.This IRL technique has been shown to be effective and efficient when applied to the classification of a collection of veterinary questionnaires.

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	ISBN: 9789832078791 Organized by: Universiti Utara Malaysia
Uncontrolled Keywords:	Machine Learning, Inductive Rule Learning, Clas sification
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Divisions:	College of Arts and Sciences
Depositing User:	Mrs. Norazmilah Yaakub
Date Deposited:	25 Aug 2014 07:02
Last Modified:	25 Aug 2014 07:02
URI:	https://repo.uum.edu.my/id/eprint/12032

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