Teaching Interactive Recommender Systems – Recommending an Excel Based Approach
Madhukar Dayal and Sanjeev Tripathi
Indian Institute of Management Indore, India
Volume 13: 2018, pp. 249-270; ABSTRACT
Recommender systems are used in multiple applications and are actively used by people to find interesting places to visit or to eat, movies to watch, books to read, and in a variety of other ways. With the growth in applications in the industry, the study of such systems has emerged as specialised courses in technical institutes, universities and more importantly, in business schools. As such, there is a need for a simple model explaining the concept and working of recommender systems and their applications to real world situations for business school students. While there has been an extensive research to improve recommender systems, little work has been done to develop pedagogical tools for teaching recommender systems. In this article we present an easy to understand model which explains the core concepts behind recommender systems. This model has been tested in class, and has interactive ability not found in existing recommender systems. This allows a user to alter preference parameters and obtain improved recommendations. We hope that this tool will be useful to educators in providing both basic and advanced knowledge to business students on recommender systems.
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