| 英文标题 | Prediction of community evolution based on long-short term memory network |
| 作者英文名 | Jiang Lele, Liu Houquan, Zhang Nan |
| 机构英文名 | School of Computer Science & Technology,China University of Mining & Technology,Xuzhou Jiangsu 221116,China |
| 英文摘要 | The network in real life is usually dynamic and the network structure evolves over time. Detecting the evolution of the community can understand the basic behavior of the network. To solve the problem of dynamic community evolution prediction, the paper proposed a community evolution prediction method based on evolutionary tree and long-short term memory network. Firstly, it extracted the multi-features of the community from the dynamic network. Then, it classified the features by using the long-short term memory network. Finally, it predicted the changes of the community in the next period of time. Experiments on two real data sets show that the proposed method can effectively predict community evolution behavior and is more competitive than other methods. |
| 英文关键词 | dynamic network; community evolution prediction; long-short term memory |