Complex Network based Recommender System

Abstract

The structural abstraction of Recommender Systems has a high resemblance as that of a Complex Network(CN). The underlining principles of the different types of Recommender Systems, such as Collaborative Filtering, Content-Based, Knowledge-Based, Utility-Based, and Hybrid are similar to the attributes and theories of Complex Networks. Considering the enormity of computation in Recommender Systems logic formulation and it's a structural similarity with Complex Networks, the research work seeks to highlight attributes of Complex Networks and Recommender Systems to suggest the applicability of theories, and principles in CN's that can be considered in the construction of Recommender Systems. The research further elaborates on matrices for checking the correctness of the use of these theories.