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Hybrid Recommender System Using Emotional Fingerprints Model

Author

Listed:
  • Anthony Nosshi

    (Mansoura University, Mansoura, Egypt)

  • Aziza Saad Asem

    (Mansoura University, Mansoura, Egypt)

  • Mohammed Badr Senousy

    (Sadat Academy for Management Sciences, Cairo, Egypt)

Abstract

With today's information overload, recommender systems are important to help users in finding needed information. In the movies domain, finding a good movie to watch is not an easy task. Emotions play an important role in deciding which movie to watch. People usually express their emotions in reviews or comments about the movies. In this article, an emotional fingerprint-based model (EFBM) for movies recommendation is proposed. The model is based on grouping movies by emotional patterns of some key factors changing in time and forming fingerprints or emotional tracks, which are the heart of the proposed recommender. Then, it is incorporated into collaborative filtering to detect the interest connected with topics. Experimental simulation is conducted to understand the behavior of the proposed approach. Results are represented to evaluate the proposed recommender.

Suggested Citation

  • Anthony Nosshi & Aziza Saad Asem & Mohammed Badr Senousy, 2019. "Hybrid Recommender System Using Emotional Fingerprints Model," International Journal of Information Retrieval Research (IJIRR), IGI Global, vol. 9(3), pages 48-70, July.
    • Handle: RePEc:igg:jirr00:v:9:y:2019:i:3:p:48-70
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