Name
Title | ||
|---|---|---|
Slanderous user detection with modified recurrent neural networks in recommender system. |
Abstract | ||
|---|---|---|
•We propose a challenging problem: slanderous user detection in recommender system.•We give a framework SDRS to solve slanderous user detection problem, which can benefit existing recommender system models.•We propose an RNN with modified GRU to make sentiment analysis, and a filtering method to detect slanderous users, and a MF-based model to make recommendation.•We conduct extensive experiments and validations on two standard datasets and two realworld collected datasets. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.ins.2019.07.081 | Information Sciences |
Keywords | Field | DocType |
Slanderous user detection,Recommender systems,Recurrent neural networks | Recommender system,Matrix decomposition,Semantic gap,Filter (signal processing),Recurrent neural network,Artificial intelligence,Fake reviews,Machine learning,Mathematics | Journal |
Volume | ISSN | Citations |
505 | 0020-0255 | 2 |
PageRank | References | Authors |
0.35 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuanbo Xu | 1 | 14 | 2.37 |
| Yongjian Yang | 2 | 39 | 14.05 |
| Jiayu Han | 3 | 37 | 7.43 |
| En Wang | 4 | 21 | 8.13 |
| Jingci Ming | 5 | 2 | 0.35 |
| Hui Xiong | 6 | 4958 | 290.62 |