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.
Description
IEEE Xplore - Evaluating Cooperation in Communities with the k-Core Structure
%0 Conference Paper
%1 giatsidis2011evaluating
%A Giatsidis, Christos
%A Thilikos, Dimitrios M.
%A Vazirgiannis, Michalis
%B Advances in Social Networks Analysis and Mining (ASONAM), 2011 International Conference on
%D 2011
%K community core k-core
%P 87-93
%R 10.1109/ASONAM.2011.65
%T Evaluating Cooperation in Communities with the k-Core Structure
%U http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5992567&tag=1
%X 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.
@inproceedings{giatsidis2011evaluating,
abstract = {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.},
added-at = {2014-01-17T15:00:55.000+0100},
author = {Giatsidis, Christos and Thilikos, Dimitrios M. and Vazirgiannis, Michalis},
biburl = {https://www.bibsonomy.org/bibtex/2e635975e729c3aee7575db0485f3e853/sdo},
booktitle = {Advances in Social Networks Analysis and Mining (ASONAM), 2011 International Conference on},
description = {IEEE Xplore - Evaluating Cooperation in Communities with the k-Core Structure},
doi = {10.1109/ASONAM.2011.65},
interhash = {ccc1059e51e6c0671f9987824e7c9f92},
intrahash = {e635975e729c3aee7575db0485f3e853},
keywords = {community core k-core},
pages = {87-93},
timestamp = {2014-01-17T15:00:55.000+0100},
title = {Evaluating Cooperation in Communities with the k-Core Structure},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5992567&tag=1},
year = 2011
}