Cluster analysis on dynamic graphs
This project describes: a novel graph clustering algorithm that is an efficient extension of the Gibbs sampling under distance-dependent Chinese Restaurant Process, ddCRP for graph, a general cluster ensemble, and a cluster matching algorithm based on the concept of Meta-Graph [32], an algorithm...
Saved in:
| 主要作者: | |
|---|---|
| 其他作者: | |
| 格式: | Final Year Project |
| 語言: | English |
| 出版: |
Nanyang Technological University
2020
|
| 主題: | |
| 在線閱讀: | https://hdl.handle.net/10356/144629 |
| 標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
| 機構: | Nanyang Technological University |
| 語言: | English |
| 總結: | This project describes: a novel graph clustering algorithm that is an efficient
extension of the Gibbs sampling under distance-dependent Chinese Restaurant
Process, ddCRP for graph, a general cluster ensemble, and a cluster matching
algorithm based on the concept of Meta-Graph [32], an algorithm pipeline to
tackle the dynamic graph clustering problem, intensive experiments to measure
performance of the new algorithms. |
|---|