Abstract:
The identification of closely connected cores in a
complex network has become an important feature in
the area of community mining in recent years.
According to the network topology, it is true that a
large and complex graph have a set of densely
connected sub-graphs as the cores. Extraction these
cores can reveal that some unexpected connection
patterns between nodes in this type of network. In this
paper, a simple and efficient intersection-based
algorithm is proposed for finding community cores in
multi-relational citation network by using the strength
of modularity-based Louvain method. The proposed
system is applied on a part of CiteseerX digital library
[5] as the real-world data set of heterogeneous
citation graph. Graph nodes represent individual
papers of CiteseerX data set which are linked by three
types of above relationships. The experimental results
show that the proposed algorithm is highly effective in
core extraction with comparable time complexity.
