Dynamic Community Detection via Relationship Extraction Strategy and Community Pedigree Mapping

• Main Authors: Peng, Cheng-Yi, 彭誠毅
• Other Authors: Lee, Suh-Yin
• Format: Others
• Language: en_US
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/84879290365286829171

碩士 === 國立交通大學 === 資訊科學與工程研究所 === 99 === Recently, considerable attention has been paid to the issue of dynamic community in dynamic social network due to its widespread applications. Many potential social phenomena, in practice, can be extracted by analyzing the dynamic social structure over time. Although there have been many recent studies proposed on dynamic community, these works, generally, partition the community based on a sequence of interaction graphs, which is usually applied to express a dynamic social network. Nevertheless, the interaction graph may be insufficient to reveal the relationship among individuals, since, in a snapshot of time slice, no interaction among individuals does not indicate no actual relationship. In this thesis, a novel algorithm EPC, which stands for relationship Extraction and community Pedigree mapping Community miner, is developed to mine the evolution of community. We present a Relationship Extraction strategy to construct a relationship graph within a defined observation window. EPC partitions communities based on relationship graph and uses proposed Community Pedigree Mapping method to discover the evolution of dynamic community in dynamic social network. The experimental results on synthetic and real datasets show that EPC not only significantly outperforms the prior studies in accuracy but also possesses graceful scalability and smoothness.