LinkBlackHole: Robust Overlapping Community Detection Using Link Embedding
LinkBlackHole: Robust Overlapping Community Detection Using Link Embedding is a scholarly work, published in 2019 in ''IEEE Transactions on Knowledge and Data Engineering''. The main subjects of the publication include complex network, mixing, peer-to-peer, data mining, link, computer science, algorithm, resilience of materials, theoretical computer science, distributed computing, embedding, cluster analysis, and sampling. The paper proposes LinkBlackHole*, a novel algorithm for finding communities that are (i) overlapping in nodes and (ii) mixing (not separating clearly) in links.