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A Prospect on an Intelligent Recommender System

Author

Listed:
  • Pooja

    (AIACTR, GGSIPU, Delhi, India & ABES Engineering College, Ghaziabad, India)

  • Vishal Bhatnagar

    (AIACTR, GGSIPU, Delhi, India)

Abstract

User satisfaction is the principle component in the prosperity of a recommender system to provide an exact recommendation within a rational amount of time. The recommendation system is an intelligent system that analyzes the large quantity of online data to predict the patterns. In this paper, various recommendation techniques are described as a literature survey and their classifications are explained based upon the attributes and characteristics required for the recommendation process. The categorization of the recommendation system hinge on the analysis of the research papers and identifies the areas of the future for the development of an intelligent system.

Suggested Citation

  • Pooja & Vishal Bhatnagar, 2021. "A Prospect on an Intelligent Recommender System," International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), IGI Global, vol. 12(2), pages 25-43, March.
    • Handle: RePEc:igg:jssmet:v:12:y:2021:i:2:p:25-43
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    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJSSMET.2021030102
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    Cited by:

    1. Phan, Dinh Hoang Bach & Tran, Vuong Thao & Iyke, Bernard Njindan, 2022. "Geopolitical risk and bank stability," Finance Research Letters, Elsevier, vol. 46(PB).
    2. Umut Erdem & K. Mert Cubukcu, 2022. "The uneven geography of innovation in Turkey: Visualizing the geography and regional relatedness of patent production," Environment and Planning A, , vol. 54(1), pages 7-10, February.

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