Reliable Community Search in Dynamic Networks
Yifu Tang, Jianxin Li, Nur Al Hasan Haldar, Ziyu Guan, Jiajie Xu,, Chengfei Liu

TL;DR
This paper introduces a new reliable community search model for dynamic weighted networks, focusing on connection strength, structural continuity, and member engagement, with algorithms that improve search efficiency and reliability.
Contribution
It proposes the $(\theta,k)$-$core$ reliable community model and develops novel online and index-based algorithms for efficient, reliable community detection in dynamic networks.
Findings
Algorithms outperform existing methods in efficiency and reliability.
The proposed methods effectively identify stable communities over time.
Extensive experiments validate the approach on real datasets.
Abstract
Searching for local communities is an important research problem that supports advanced data analysis in various complex networks, such as social networks, collaboration networks, cellular networks, etc. The evolution of such networks over time has motivated several recent studies to identify local communities in dynamic networks. However, these studies only utilize the aggregation of disjoint structural information to measure the quality and ignore the reliability of the communities in a continuous time interval. To fill this research gap, we propose a novel - reliable community (CRC) model in the weighted dynamic networks, and define the problem of \textit{most reliable community search} that couples the desirable properties of connection strength, cohesive structure continuity, and the maximal member engagement. To solve this problem, we first develop a novel edge…
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Taxonomy
TopicsPeer-to-Peer Network Technologies · Opportunistic and Delay-Tolerant Networks · Energy Efficient Wireless Sensor Networks
