An Efficient Updation Approach for Enumerating Maximal (Ī”, γ)Cliques of a Temporal Network

07/08/2020
āˆ™
by   Suman Banerjee, et al.
āˆ™
0
āˆ™

Given a temporal network š’¢(š’±, ā„°, š’Æ), (š’³,[t_a,t_b]) (where š’³āŠ†š’±(š’¢) and [t_a,t_b] āŠ†š’Æ) is said to be a (Ī”, γ)clique of š’¢, if for every pair of vertices in š’³, there must exist at least γ links in each Ī” duration within the time interval [t_a,t_b]. Enumerating such maximal cliques is an important problem in temporal network analysis, as it reveals contact pattern among the nodes of š’¢. In this paper, we study the maximal (Ī”, γ)clique enumeration problem in online setting; i.e.; the entire link set of the network is not known in advance, and the links are coming as a batch in an iterative manner. Suppose, the link set till time stamp T_1 (i.e., ā„°^T_1), and its corresponding (Ī”, γ)-clique set are known. In the next batch (till time T_2), a new set of links (denoted as ā„°^(T_1,T_2]) is arrived.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset
Success!
Error Icon An error occurred

Sign in with Google

×

Use your Google Account to sign in to DeepAI

×

Consider DeepAI Pro