Discover the Maximum Descriptive User Groups on the Social Web

Product reviews in E-commerce websites such as restaurants‎, ‎movies‎, ‎E-commerce products‎, ‎etc.‎, ‎are essential resources for consumers to make purchasing decisions on various items‎. ‎In this paper‎, ‎we model discovering groups with maximum descriptively from E-commerce website of the form ‎, ‎where i\in \mathcal{I} (the set of items or products)‎, ‎u\in \mathcal{U} (the set of users) and s is the integer rating that user u has assigned to the item i‎. ‎Labeled groups from user's attributes are found by solving an optimization problem‎. ‎The performance of the approach is examined by some experiments on real data-sets‎.

Keywords:

maximum descriptively , Optimization , user group discovery , rating record