Classifying consumer regulatory focus by analyzing small and imbalanced web shopping logs

초록

In this research, we propose a method to learn a classifier for consumer's regulatory focus on the small and class imbalanced web shopping logs for applying it to personalized recommendations. For this purpose, we define the consumer's behavior variables, utilitarian preference index, and information exploration activity index by analyzing the web shopping logs. We then use these variables as inputs to learn the classifier for predicting the consumer's regulatory focus. According to the experiment results, the proposed method outperforms the existing methods on small and class imbalanced data sets. © 2013 International Information Institute.

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