Title :
K-clique community detection based on union-find
Author :
Fu Cai ; Zhang Kang ; Fang Zhicun ; Han Lansheng ; Chen Jing
Author_Institution :
Sch. of Comput. Sci. & Technol., HuaZhong Univ. of Sci. & Technol., Wuhan, China
Abstract :
As network community becoming increasingly complicated, the effective and fast community detection algorithm gets more important in network analysis. In this paper, a improved k-clique detection algorithm based on union-find structure is proposed, the time efficiency of community discovery in highly overlapped complex network is improved and it is possible to divide all communities within approximately linear time complexity. In this algorithm, we use union-find structure to store divided communities and reduce the number of unnecessary intersection test. The experiments result on the real data sets show that the algorithm is reasonable and effective, and its time efficiency is better than other overlapping community algorithms.
Keywords :
data analysis; data mining; community detection algorithm; complex network; improved k-clique detection algorithm; linear time complexity; real data sets; time efficiency; union-find structure; Algorithm design and analysis; Arrays; Communities; Complex networks; Detection algorithms; Partitioning algorithms; Time complexity; k-clique; network community; union-find structure;
Conference_Titel :
Computer, Information and Telecommunication Systems (CITS), 2014 International Conference on
Conference_Location :
Jeju
Print_ISBN :
978-1-4799-4384-5
DOI :
10.1109/CITS.2014.6878972