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Isolation concepts applied to temporal clique enumeration

Published online by Cambridge University Press:  16 October 2020

Hendrik Molter*
Affiliation:
TU Berlin, Faculty IV, Algorithmics and Computational Complexity (emails: rolf.niedermeier@tu-berlin.de, m.renken@tu-berlin.de)
Rolf Niedermeier
Affiliation:
TU Berlin, Faculty IV, Algorithmics and Computational Complexity (emails: rolf.niedermeier@tu-berlin.de, m.renken@tu-berlin.de)
Malte Renken
Affiliation:
TU Berlin, Faculty IV, Algorithmics and Computational Complexity (emails: rolf.niedermeier@tu-berlin.de, m.renken@tu-berlin.de)
*
*Corresponding author. Email: h.molter@tu-berlin.de
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Abstract

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Isolation is a concept originally conceived in the context of clique enumeration in static networks, mostly used to model communities that do not have much contact to the outside world. Herein, a clique is considered isolated if it has few edges connecting it to the rest of the graph. Motivated by recent work on enumerating cliques in temporal networks, we transform the isolation concept to the temporal setting. We discover that the addition of the time dimension leads to six distinct natural isolation concepts. Our main contribution is the development of parameterized enumeration algorithms for five of these six isolation types for clique enumeration, employing the parameter “degree of isolation.” In a nutshell, this means that the more isolated these cliques are, the faster we can find them. On the empirical side, we implemented and tested these algorithms on (temporal) social network data, obtaining encouraging results.

Information

Type
Research Article
Copyright
© The Author(s), 2020. Published by Cambridge University Press