Abstract
Recommender Systems (RS) are computer-based tools that use Artificial Intelligence (AI) algorithms to make product or service recommendations to users. A recommendation algorithm is usually applied to predict users’ tastes and preferences based on their behavioral characteristics. RS has gained the attention of e-retailers and managers connected to e-business. This research aims to provide a holistic and deep understanding of RS concerning its current progress and future scope. Hence, the goal of the study is to review the various trends and developments that have taken place in the field of RS in the last decade. Also, it outlines the key future scope and its application in various domains. For this purpose, a comprehensive and systematic literature review has been conducted using recently developed Scientific Procedures and Rationales for Systematic Literature Reviews (SPAR-4-SLR). A total of 60 journal articles and conference proceedings published from 2010 to 2022 under top publishers have been selected. The extant literature has been scrutinized and research gaps have been identified. Furthermore, this paper also envisions the future of RS, which may broaden the horizon for new research directions in this field.
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Bokadia, S., Jain, R. (2024). Metamorphosis of Recommender Systems: Progressive Inclusion of Consumers. In: Sharma, S.K., Dwivedi, Y.K., Metri, B., Lal, B., Elbanna, A. (eds) Transfer, Diffusion and Adoption of Next-Generation Digital Technologies. TDIT 2023. IFIP Advances in Information and Communication Technology, vol 699. Springer, Cham. https://doi.org/10.1007/978-3-031-50204-0_28
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