How Machine Learning is Innovating Today's World

23A Survey on Domain of Application of Recommender System

Sudipto Dhar

Department of Computer Science & Engineering, University of Engineering and Management, Kolkata, West Bengal, India

Abstract

To assist consumers in finding products that fit their interests and preferences, recommender systems have been developed. The absence of a proper survey to demonstrate the uses of recommender systems led to the description of the foundations of recommender systems in this article, along with some of its most significant applications that are crucial to modern living. In order to create high-performance recommendation systems, the benefits and drawbacks of recently offered methods have also been considered. Individual and group recommender systems are the two main categories. Both system types have been considered in this study. There is also discussion and analysis of the most modern methodologies in the field of recommender systems.

Keywords: Recommendation system, implicit feedback, explicit feedback

23.1 Introduction

We are now inundated with data and information. Sources of information include the World Wide Web [1], trading sites with a large number of customers, and sites with thousands of things [36]. This quantity of data will be uploaded every day, causing information avalanche [2]. Information overload and selection technique (to choose from various sectors such as items) are seen as a difficulty; the decision should be made by a customer, and in many circumstances, merchants ...