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Bipartite Graph Analysis as an Alternative to Reveal Clusterization in Complex Systems
2018
2018 IEEE Second International Conference on Data Stream Mining & Processing (DSMP)
We demonstrate how analysis of co-clustering in bipartite networks may be used as a bridge to connect, compare and complement clustering results about community structure in two different spaces: single-mode bipartite network projections. As a case study we consider scientific knowledge, which is represented as a complex bipartite network of articles and related concepts. Connecting clusters of articles and clusters of concepts via article-to-concept bipartite co-clustering, we demonstrate how
doi:10.1109/dsmp.2018.8478505
fatcat:foguoixjlfconhjwuusj2yvowe