Visual exploration of collaboration networks based on graph degeneracy
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Advanced graph mining for community evaluation in social networks and the web
Proceedings of the sixth ACM international conference on Web search and data mining
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Streaming algorithms for k-core decomposition
Proceedings of the VLDB Endowment
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Community sub graphs are characterized by dense connections or interactions among its nodes. Community detection and evaluation is an important task in graph mining. A variety of measures have been proposed to evaluate the quality of such communities. In this paper, we evaluate communities based on the k-core concept, as means of evaluating their collaborative nature - a property not captured by the single node metrics or by the established community evaluation metrics. Based on the k-core, which essentially measures the robustness of a community under degeneracy, we extend it to weighted graphs, devising a novel concept of k-cores on weighted graphs. We applied the k-core approach on large real world graphs--such as DBLP and report interesting results.