There are 2 repositories under local-community-detection topic.
Local Community Detection in Multiple Netwrks
Code for paper "Searching for polarization in signed graphs: a local spectral approach" (published at WebConf 2020)
Fast Local Community Discovery: Relying on the Strength of Links
Local Lanczos Spectral Approximation for Community Detection
Krylov Subspace Approximation for Local Community Detection in Large Networks
Locally-biased Spectral Approximation for Community Detection
Local community detection for a given set of query nodes attracts much research attention recently. The query nodes play essential roles in the detection effectiveness. Existing methods perform well when a query node is from the target community core region. However, they struggle with the query- bias issue and especially perform unsatisfactorily when the query nodes come from different communities or when certain query nodes are from communities overlapping region or community boundary region. To address above issues, we consider from a new angle, to replace these original “intractable” query nodes with new detection-friendly query nodes. In this paper, we propose an effective ATP (Amplified Topology Potential) algorithm to detect core nodes of the target communities w.r.t. original query nodes. For one query node, ATP first builds a query-oriented topology potential field around the query node by aggregating random walk with restart scores. Then it amplifies the topology potential value to make core nodes of target communities easily distinguished. Graph-size-independent fast approximation strategies are also proposed together with sound theoretical foundations. Extensive experiments on four real networks using ten state-of-the-art local community detection methods verify the improvement in detection effectiveness and efficiency by the replacing strategy for the tough query cases. Please refer to the ICDM 2020 paper (Rethinking Local Community Detection: Query Nodes Replacement) for details.
This repository includes my project in Python for the Advanced Software Praktika in Data and Text Mining at the University of Heidelberg
Detecting Overlapping Communities from Local Spectral Subspaces