Title :
Mining maximal cliques from an uncertain graph
Author :
Mukherjee, Arko Provo ; Pan Xu ; Tirthapura, Srikanta
Author_Institution :
Dept. of Electr. & Comput. Eng., Iowa State Univ., Ames, IA, USA
Abstract :
We consider mining dense substructures (maximal cliques) from an uncertain graph, which is a probability distribution on a set of deterministic graphs. For parameter 0 <; α <; 1, we consider the notion of an α-maximal clique in an uncertain graph. We present matching upper and lower bounds on the number of α-maximal cliques possible within a (uncertain) graph. We present an algorithm to enumerate α-maximal cliques whose worst-case runtime is near-optimal, and an experimental evaluation showing the practical utility of the algorithm.
Keywords :
data mining; graph theory; probability; deterministic graphs; mining dense substructures; mining maximal cliques; probability distribution; uncertain graph; worst case runtime; Algorithm design and analysis; Communities; Data mining; Moon; Proteins; Runtime; Social network services;
Conference_Titel :
Data Engineering (ICDE), 2015 IEEE 31st International Conference on
Conference_Location :
Seoul
DOI :
10.1109/ICDE.2015.7113288