Title of article :
Discover Maximum Descriptive User Groups on the Social Web
Author/Authors :
Abbasi, Z. School of Mathematics and Computer Science - Damghan University - Damghan - Iran , Akhoundi, N. School of Mathematics and Computer Science - Damghan University - Damghan - Iran
Abstract :
Abstract. 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 < i,u, s >, where i ∈ I (the set of items or products), u ∈ U (the
set of users) and s is the integer rating that user u has assigned to the item
i. Labeled groups from user attributes are found by solving an optimization
problem. The performance of the approach is examined by some experiments
on real data-sets.
Keywords.
Keywords :
Maximum descriptively , Optimization , User group discovery , Rating record
Journal title :
Control and Optimization in Applied Mathematics