Contextual Personality-aware Recommender System Versus Big Data Recommender System

Abstract

Many personality theories suggest that personality influences c ustomer shopping preference. Thus, this research analyses the potential ability to improve the accuracy of the collaborative filtering r ecommender s ystem b y i ncorporating t he F ive-Factor M odel personality traits data obtained from customer text reviews. The study uses a large Amazon dataset with customer reviews and information about verified c ustomer product p urchases. 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.