Name
Title | ||
|---|---|---|
Using hybrid normalization technique and state transition algorithm to VIKOR method for influence maximization problem |
Abstract | ||
|---|---|---|
Influence maximization problem is the procedure of attempting to identify a group of K nodes in a social network in order to maximize the dissemination of influence under certain influence models. Based on state transition algorithm (STA) and a multiple criteria decision making (MCDM) method called Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR), a novel hybrid approach has been proposed to cope with the influence maximization problem in this paper. Firstly, an intelligent optimization paradigm called STA is introduced to obtain the most appropriate weights that are used to integrate the criteria of each alternative in the VIKOR method. Then, a hybrid normalization technique has been presented to allow the process of aggregating criterion with numerical and comparable data properly in this method. Several typical networks have been used to testify the effectiveness of proposed method and technique. Compared with other approaches, experimental results show that our approach can solve the influence maximization problem more effectively. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.neucom.2020.05.084 | Neurocomputing |
Keywords | DocType | Volume |
Influence maximization,Normalization technique,Multiple criteria decision making,State transition algorithm | Journal | 410 |
ISSN | Citations | PageRank |
0925-2312 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaojun Zhou | 1 | 86 | 16.24 |
| Rundong Zhang | 2 | 0 | 0.34 |
| Ke Yang | 3 | 0 | 0.34 |
| Chunhua Yang | 4 | 435 | 71.63 |
| Tingwen Huang | 5 | 5684 | 310.24 |