Abstract
Recommendation System (RS) gains considerable popularity from the past decade in E-Commerce and other allied fields. This paper investigates the various traditional Recommendation System like Content-based (CB), Collaboration Filtering-based (CF), Demographic-based, Knowledge-based and discussed current trends in recommendation system like location-aware, context-aware, and Deep Learning techniques. Various improvements and limitations in Recommendation systems have been listed out with evolution metrics for analyzing the accuracy of the algorithms. This paper well-elaborated for the past, present and future scope of the Recommendation System which would be useful for researchers to get familiarity with this domain.
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CITATION STYLE
Addagarla, S. K., & Amalanathan, A. (2019). A survey on comprehensive trends in recommendation systems & applications. International Journal of Electronic Commerce Studies, 10(1), 65–88. https://doi.org/10.7903/ijecs.1705
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