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Fuzzy Gravitational Search Approach to a Hybrid Data Model Based Recommender System

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Knowledge Science, Engineering and Management (KSEM 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11061))

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Abstract

In recent times, when the Internet is flooded with information, users get overwhelmed with the large amount of data and need some system to narrow down their choices. Recommender systems provide personalized suggestions to the users, giving them a better experience. Data Filtering methods along with many Computational Intelligence (CI) techniques have been used to build and optimize these systems. Here, we introduce a new Recommender System, based on Fuzzy Gravitational Search Algorithm using Hybrid Data Model (FGSA-HDM). FGSA-HDM uses a nature inspired heuristic technique, Gravitational Search Algorithm (GSA), to learn a user’s preference and optimize weightage given to different features which define the user profile. Also, to incorporate the fuzziness of human nature, these features have been represented by Fuzzy sets. The proposed technique, FGSA-HDM, has shown better results than the previously implemented techniques - Pearson Correlation based Collaborative Filtering (PCF), Fuzzy Collaborative Filtering (FCF), Fuzzy Genetic Algorithm based Collaborative Filtering (FG-CF) and Fuzzy Particle Swarm Optimization based Collaborative Filtering (FPSO-CF).

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Authors and Affiliations

  1. Samsung India Electronics Pvt Ltd, Noida, UP, India

    Shruti Tomer

  2. Netaji Subhas Institute of Technology, Sector-3, Dwarka, Delhi, 110078, India

    Sushama Nagpal

  3. Adobe Systems India Pvt Ltd, Noida, UP, India

    Simran Kaur Bindra

  4. Expedia Online Travel Svc Pvt Ltd, Gurugram, Haryana, India

    Vipra Goel

Authors
  1. Shruti Tomer
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  2. Sushama Nagpal
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  3. Simran Kaur Bindra
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  4. Vipra Goel
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Corresponding author

Correspondence to Vipra Goel .

Editor information

Editors and Affiliations

  1. University of Bristol, Bristol, United Kingdom

    Weiru Liu

  2. Università di Trento, Povo, Italy

    Fausto Giunchiglia

  3. Jilin University, Changchun, China

    Bo Yang

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Tomer, S., Nagpal, S., Bindra, S.K., Goel, V. (2018). Fuzzy Gravitational Search Approach to a Hybrid Data Model Based Recommender System. In: Liu, W., Giunchiglia, F., Yang, B. (eds) Knowledge Science, Engineering and Management. KSEM 2018. Lecture Notes in Computer Science(), vol 11061. Springer, Cham. https://doi.org/10.1007/978-3-319-99365-2_30

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  • DOI: https://doi.org/10.1007/978-3-319-99365-2_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-99364-5

  • Online ISBN: 978-3-319-99365-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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