FRecS -Financial Recommender System

Abstract

People invest their income in different schemes and funds for future use and to fulfill their daily requirements. In today's fast-paced life, recommender systems are gaining a lot of attention because they can assist people in finding information about a product that they like. In the literature, no system till date is available for suggesting people how to save their money and also help in deciding if they are buying the right product. FrecS, the algorithm presented in this paper introduces a Collaborative Filtering (CF) approach, which is a technique used for generating high quality and accurate recommendations for the user. CF uses a subset of users who are called neighborhood users to get filtered recommendations for the current user. Moreover, this system utilizes the technique of simple heuristics to provide results, which in turn assist the user in getting a better recommendation without giving much details about them, which also helps them in securing their privacy. Online evaluation and the recommender technique is the basis of the empirical assessment in this system.