ValuePick: Towards a Value-Oriented Dual-Goal Recommender System

Given a user in a social network, which new friends should we recommend, the dual goal being to achieve user satisfaction and good network connectivity? Similarly, which new products are better to recommend to satisfy customers' taste/needs as well as increase vendor profit? Typical recommender systems use merely past purchases, product ratings, demographic meta-data, and network `proximity' to make recommendations. This traditional approach, however, does not take into account the profitability of products to vendors in a customer-product network, or the efficacy of new links in a social network. We argue that it is more appropriate to view the problem of generating recommendations as an optimization problem. In this paper, (a) we propose ValuePick, a framework which incorporates the `value' of recommendations into the system while still providing accurate recommendations that retain user trust; (b) our method is parsimonious (requires only a single parameter ), flexibl...

• Type: Journal
• Year: 2010
• Where: ICDM
• Authors: Leman Akoglu, Christos Faloutsos
• Keywords: Customer-product Networks, Data Mining, ICDM 2010, Social Networks, User Satisfaction