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A \emph{Temporal Network} (also known as \emph{Link Stream} or\emph{Time-Varying Graph}) is often used to model a time-varying relationshipamong a group of agents. It is typically represented as a collection oftriplets of the form $(u,v,t)$ that denotes the interaction between the agents$u$ and $v$ at time $t$. For analyzing the contact patterns of the agentsforming a temporal network, recently the notion of classical \textit{clique} ofa \textit{static graph} has been generalized as \textit{$\Delta$\mbox{-}Clique}of a Temporal Network. In the same direction, one of our previous studiesintroduces the notion of \textit{$(\Delta, \gamma)$\mbox{-}Clique}, which isbasically a \textit{vertex set}, \textit{time interval} pair, in which everypair of the clique vertices are linked at least $\gamma$ times in every$\Delta$ duration of the time interval. In this paper, we propose a differentmethodology for enumerating all the maximal $(\Delta, \gamma)$\mbox{-}Cliquesof a given temporal network. The proposed methodology is broadly divided intotwo phases. In the first phase, each temporal link is processed forconstructing $(\Delta, \gamma)$\mbox{-}Clique(s) with maximum duration. In thesecond phase, these initial cliques are expanded by vertex addition to form themaximal cliques. From the experimentation carried out on $5$ real\mbox{-}worldtemporal network datasets, we observe that the proposed methodology enumeratesall the maximal $(\Delta,\gamma)$\mbox{-}Cliques efficiently, particularly whenthe dataset is sparse. As a special case ($\gamma=1$), the proposed methodologyis also able to enumerate $(\Delta,1) \equiv \Delta$\mbox{-}cliques with muchless time compared to the existing methods.

First Stretch then Shrink and Bulk: A Two Phase Approach for Enumeration of Maximal $(\Delta, \gamma)$\mbox{-}Cliques of a Temporal Network