Contextual Personality-Aware Recommender System Versus Big Data Recommender System

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Contextual Personality-Aware Recommender System Versus Big Data Recommender System
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CC Attribution 4.0 International:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
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2021
Language
English

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Abstract
Many personality theories suggest that personality influences customer shopping preference. Thus, this research analyses the potential ability to improve the accuracy of the collaborative filtering recommender system by incorporating the Five-Factor Model personality traits data obtained from customer text reviews. The study uses a large Amazon dataset with customer reviews and information about verified customer product purchases. However, evaluation results show that the model leveraging big data by using the whole Amazon dataset provides better recommendations than the recommender systems trained in the contexts of the customer personality traits.
Keywords Recommender system Predictive modelling Big five, Personality traits Big data analytics Amazon dataset

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