Discover the Maximum Descriptive User Groups on the Social Web

نویسندگان

1 School of mathematics and computer science, Damghan university, Damghan, Iran

2 School of mathematics and computer science, Damghan university, Damghan, Iran

doi
10.30473/coam.2020.49118.1127
چکیده

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 $i\in \mathcal{I}$ (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.