Mining Top-K Influencers in Social Networks on Heterogeneous Communities
碩士 === 國立中正大學 === 資訊工程研究所 === 103 === In this thesis, we discuss how to find top-K influencers in social networks based on the different rates of diffusion between heterogeneous communities. The different rates of diffusion means that when influence spreads to other communities, the influence will b...
Main Authors: | , |
---|---|
Other Authors: | |
Format: | Others |
Language: | en_US |
Published: |
2015
|
Online Access: | http://ndltd.ncl.edu.tw/handle/86878388130131857335 |