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The State of the Art Techniques in Recommendation Systems

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Applied Computational Technologies (ICCET 2022)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 303))

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Abstract

The fast increment in the measure of information over the internet has made it hard to discover entities that might hold any importance with users. Thus, information has expanded at an unpredicted rate, and the information over-burden issue has turned out to be progressively severe for online users. One answer for this information over-burden issue is the utilization of Recommendation Systems (RSs). Recommendation System is a capable technology that tries to anticipate users’ interests by providing them with the information or services they require without directly enquiring. Recommendation systems are used by most social media services and e-commerce applications to improve user convenience. RS helps to explore options and decrease information overload for online users. This paper presents a complete survey of recommendation systems. This paper forms a platform for researchers in the recommendation system domain and provides collective discussions over various techniques.

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Authors and Affiliations

  1. Department of Technology, Shivaji University, Kolhapur, Maharashtra, India

    Chetan Awati

  2. DKTEs, Textile and Engineering Institute, Ichalkaranji, Maharashtra, India

    Suresh Shirgave

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  1. Chetan Awati
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  2. Suresh Shirgave
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Correspondence to Chetan Awati .

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Editors and Affiliations

  1. Department of Electronics and Telecommunication Engineering, Dr. B. A. Technological University, Lonere, Maharashtra, India

    Brijesh Iyer

  2. Department of Digital Education and Policy, Swansea University, Swansea, UK

    Tom Crick

  3. Creative Technologies and Product Design, National Taipei University of Business, Taipei City, Taiwan

    Sheng-Lung Peng

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Awati, C., Shirgave, S. (2022). The State of the Art Techniques in Recommendation Systems. In: Iyer, B., Crick, T., Peng, SL. (eds) Applied Computational Technologies. ICCET 2022. Smart Innovation, Systems and Technologies, vol 303. Springer, Singapore. https://doi.org/10.1007/978-981-19-2719-5_68

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