Collaborative Filtering based simple restaurant recommender

This paper proposes a basic structure and steps of designing a recommender system that uses Collaborative Filtering (user based) along with applications of partitioning and clustering of data, thus designing a Restaurant Recommender System.

Abstract

The use of Collaborative Filtering is becoming very popular in designing a simple yet efficient recommender system. A recommender system based on Collaborative Filtering basically predicts a user's interest in some item on the basis of the scores generated and the correlation calculated between the users. In this paper we propose a basic structure and steps of designing a recommender system that uses Collaborative Filtering (user based) along with applications of partitioning and clustering of data, thus designing a Restaurant Recommender System. The proposed system reduces the complexity and gives a clear view of the basic approach to build a recommender system from scratch.