What are k-cores and f-cores?
Abstract - Community subgraphs 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 our research, 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 - called f-cores.
We applied the k-core approach on large real world graphs - such as DBLP and
report interesting results.
Christos Giatsidis, Dimitrios M. Thilikos, Michalis Vazirgiannis: Evaluating Cooperation in Communities with the k-Core Structure. ASONAM 2011: 87-93
Relevant ACM KDD 2012 Demo track paper:
Christos Giatsidis, Klaus Berberich, Dimitrios M. Thilikos, Michalis Vazirgiannis: Visual exploration of collaboration networks based on graph degeneracy. KDD 2012: 1512-1515
In the following links we present visualizations from the k-core and f-core hop-1 findings for authors that are in the DBLP dataset.
This is a video displaying the above f-core DBLP demo
Video for the KDD 2012 DEMO Track
Additionally we present visualizations from the f-core hop-1 findings for authors that are in the ARXIV (High Energy Physics - Theory) dataset.
- f-cores (arxiv)
What are D-cores?
Abstract-Community detection and evaluation is an important
task in graph mining. In many cases, a community is
defined as a subgraph characterized by dense connections or
interactions among its nodes. A large variety of measures have
been proposed to evaluate the quality of such communities - in
most cases ignoring the directed nature of edges. In this paper,
we introduce novel metrics for evaluating the collaborative
nature of directed graphs - a property not captured by
the single node metrics or by other established community
evaluation metrics. In order to accomplish this objective, we
capitalize on the concept of graph degeneracy and define a
novel D-core framework, extending the classic graph-theoretic
notion of k-cores for undirected graphs to directed ones. Based
on the D-core, which essentially can be seen as a measure of
the robustness of a community under degeneracy, we devise a
wealth of novel metrics used to evaluate graph collaboration
features of directed graphs. We applied the D-core approach
on large real-world graphs such as Wikipedia and DBLP and
report interesting results at the graph as well at node level.
Christos Giatsidis, Dimitrios M. Thilikos, Michalis Vazirgiannis: D-cores: Measuring Collaboration of Directed Graphs Based on Degeneracy. ICDM 2011: 201-210
Journal Version:
D-cores: measuring collaboration of directed graphs based on degeneracy Christos Giatsidis, Dimitrios M. Thilikos, Michalis Vazirgiannis in Knowledge and Information Systems, September 2012, 10.1007/s10115-012-0539-0
In the following link we present a visualization of the D-core frontier for authors that are in the DBLP dataset.
- D-cores
- D-cores (NEW DBLP 2013)
- D-cores (Wikipedia 2013)
- D-cores (Arnetminer Citations)