In the realm of Information Technology, recommendation engines are a blooming term. The earliest recommender applications was developed in the mid-1990s, have taken us into a world of unlimited opportunities and potentialities. A Recommendation Engine or a Recommendations system are those systems that can foresee, propose items, make recommendations and provide suggestions about new items to the user while searching for and selecting various products online. Computational recommender systems have materialized to address a wide spectrum of issues over the Web. This paper gives a general idea of the multifaceted concept of recommendation systems, model, and bestow upon quite a few approaches in the recommendation process. This paper also exemplifies the practice of such approaches in numerous application areas where diverse types of perception are exploited. This paper concludes by explaining some of the key factors affecting the accuracy of recommendation systems. © Research India Publications.
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L. Nitha, “A perspective evaluation of the facets affecting the accuracy of recommendation engines”, International Journal of Applied Engineering Research, vol. 10, pp. 2029-2033, 2015.