Co-Clustering Signed 3-Partite Graphs

Koc S. S., Toroslu I. H., Davulcu H.

8th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), San-Francisco, Costa Rica, 18 - 21 August 2016, pp.945-948 identifier

  • Publication Type: Conference Paper / Full Text
  • City: San-Francisco
  • Country: Costa Rica
  • Page Numbers: pp.945-948
  • Middle East Technical University Affiliated: Yes


In this paper, we propose a new algorithm, called STRICLUSTER, to find tri-clusters from signed 3-partite graphs. The dataset contains three different types of nodes. Hyperedges connecting three nodes from three different partitions represent either positive or negative relations among those nodes. The aim of our algorithm is to find clusters with strong positive relations among its nodes. Moreover, negative relations up to a certain threshold is also allowed. Also, the clusters can have no overlapping hyperedges. We show the effectiveness of our algorithm via several experiments.