Recommendation system based on product purchase analysis

With the advent of online marketplaces, the buying practices have changed. The Amazon co-purchase network provides us with dynamic snapshots of co-purchases. We analyse the various properties of the graph like clustering co-efficient, degree distributions, etc. and try to reason out the underlying relation between such distributions. In an attempt to understand the motifs in buying pattern, we propose algorithms to mine patterns of interest. In the end, we take into account all these various parameters and develop recommendation algorithms to suit the needs of the customers.