Recommender using Hybrid Approach for Candidate Generation

Recommender systems (RS) is a very major part to contributing electronic commerce stores by recommending useful suggestions to the users based on the use of databases. Users are continuously come across with situations in which they have many options to choose and need help exploring or sorting down the possibilities. A recommendation system helps user's find compelling content in a large corpus. Candidate generation is the first stage of recommendation. The system generates a set of appropriate candidates. There are two approach for candidate generation-content-based filtering and collaborative filtering. This paper proposes a system which makes use of both the approaches for better results.