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
Pages :
10
From page :
39
To page :
48
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
Serial Year :
2019
Record number :
2546749
Link To Document :
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