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A Experimental Study on the Development of a Book Recommendation System Using Automatic Classification, Based on the Personality Type

  • Journal of Korean Library and Information Science Society
  • Abbr : JKLISS
  • 2017, 48(2), pp.215-236
  • DOI : 10.16981/kliss.48.2.201706.215
  • Publisher : Korean Library And Information Science Society
  • Research Area : Interdisciplinary Studies > Library and Information Science
  • Received : May 19, 2017
  • Accepted : June 3, 2017

Hyun Yang Cho 1

1경기대학교

Accredited

ABSTRACT

The purpose of this study is to develop an automatic classification system for recommending appropriate books of 9 enneagram personality types, using book information data reviewed by librarians. Data used for this study are book review of 501 recommended titles for children and young adults from National Library for Children and Young Adults. This study is implemented on the assumption that most people prefer different types of books, depending on their preference or personality type. Performance test for two different types of machine learning models, nonlinear kernel and linear kernel, composed of 360 clustering models with 6 different types of index term weighting and feature selections, and 10 feature selection critical mass were experimented. It is appeared that LIBLINEAR has better performance than that of LibSVM(RBF kernel). Although the performance of the developed system in this study is relatively below expectations, and the high level of difficulty in personality type base classification take into consideration, it is meaningful as a result of early stage of the experiment.

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