Utilizing Popularity Characteristics for Product Recommendation

Hyung Jun Ahn
International Journal of Electronic Commerce,
Volume 11, Number 2, Winter 2006-07, pp. 59.

Abstract: This paper presents a novel approach to automated product recommendation based on the popularity characteristics of products. Popularity plays a significant role in the consumer purchasing process but has not been given much attention in recommendation research. A three-dimensional model of popularity is used to develop popularity classes of products. These are joined with the MovieLens dataset to create a hybrid movie recommendation system that combines genre and popularity information. As compared with collaborative filtering, the hybrid system shows positive results under the conditions of data sparsity and cold-starting. Many interesting issues for further research are suggested.

Key Words and Phrases: Automated product recommendation, cold-starting, hybrid recommender system, naive Bayesian, popularity-based recommendation, popularity model, sparsity.