Title :
Correlation k-clustering with pre-clustered items on cactus graphs
Author :
Shuguang, Li ; Xiao, Xin
Author_Institution :
Coll. of Comput. Sci. & Technol., Shandong Inst. of Bus. & Technol., Yantai, China
Abstract :
Given a graph G = (V, E) with real-valued edge weights, the problem of correlation k-clustering with pre-clustered items is to extend a k-clustering of distinguished vertices of G (pre-clustered items) to partition all the vertices into clusters so as to minimize the total absolute weight of cut positive edges and uncut negative edges. This problem for general graphs is APX-complete. A polynomial time exact algorithm for cactus graphs is presented.
Keywords :
computational complexity; graph theory; optimisation; pattern clustering; set theory; APX-complete; cactus graph; correlation k-clustering; Approximation algorithms; Approximation methods; Clustering algorithms; Computer science; Correlation; Cost function; Polynomials; algorithms; cactus graphs; correlation k-clustering; pre-clustered items;
Conference_Titel :
Computer Science and Education (ICCSE), 2010 5th International Conference on
Conference_Location :
Hefei
Print_ISBN :
978-1-4244-6002-1
DOI :
10.1109/ICCSE.2010.5593807