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Emotion Distribution Profile for Movies Recommender Systems

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Communication and Intelligent Systems

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 204))

Abstract

Reviews, comments and feedbacks are user-generated content which comprises of insights regarding a given item or a thing and furthermore user’ emotions. Various highlights of user-created content incorporate feelings, opinions and survey helpfulness that shows a promising research in the field of recommender systems. Reviews contain various words and sentences that show their natural passionate substance. Emotions are a significant component of human conduct. They enable us for decision making by generating a liking or disliking toward a particular item. This paper harnesses reviews as the content generated from user to exploit, emotion as a basis for generating recommendations. Through experiments conducted on real dataset, our proposed approach compares the performance with traditional item-based collaborative filtering approach. Experimental results show 173% increase in prediction accuracy for top 25 recommendations as compared to prediction accuracy based on rating-based item similarity.

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Author information

Authors and Affiliations

  1. ABES Engineering College, Ghaziabad, U.P., India

    Mala Saraswat

  2. Netaji Subhas University of Technology, Delhi, India

    Shampa Chakraverty

Authors
  1. Mala Saraswat
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  2. Shampa Chakraverty
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Rajasthan Technical University, Kota, Rajasthan, India

    Harish Sharma

  2. Department of Computer Science and Engineering, Swami Keshvanand Institute of Technology, Jaipur, India

    Mukesh Kumar Gupta

  3. Birla Institute of Applied Sciences, Nainital, Uttarakhand, India

    G. S. Tomar

  4. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore

    Wang Lipo

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© 2021 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Saraswat, M., Chakraverty, S. (2021). Emotion Distribution Profile for Movies Recommender Systems. In: Sharma, H., Gupta, M.K., Tomar, G.S., Lipo, W. (eds) Communication and Intelligent Systems. Lecture Notes in Networks and Systems, vol 204. Springer, Singapore. https://doi.org/10.1007/978-981-16-1089-9_30

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  • DOI: https://doi.org/10.1007/978-981-16-1089-9_30

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-1088-2

  • Online ISBN: 978-981-16-1089-9

  • eBook Packages: EngineeringEngineering (R0)

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