Graph Data Storage Model for Recommender System

Increasing e-commerce data presents new challenges for storing and querying large amounts of data to online recommendation systems. Recent studies on recommendation systems show that graph data model is more efficient than relational data model for processing complex data. This paper proposes a new graph data storage model for the collaborative filtering-based recommendation system. We present our structure, algorithm and experimental results. The result of the experiment shows that proposed approach is efficient storage model for recommendation system.