TY - GEN
T1 - Cluster editing in multi-layer and temporal graphs
AU - Chen, Jiehua
AU - Molter, Hendrik
AU - Sorge, Manuel
AU - Suchý, Ondřej
N1 - Publisher Copyright:
© Jiehua Chen, Hendrik Molter, Manuel Sorge, and Ondřej Suchý;
PY - 2018/12/1
Y1 - 2018/12/1
N2 - Motivated by the recent rapid growth of research for algorithms to cluster multi-layer and temporal graphs, we study extensions of the classical Cluster Editing problem. In Multi-Layer Cluster Editing we receive a set of graphs on the same vertex set, called layers and aim to transform all layers into cluster graphs (disjoint unions of cliques) that differ only slightly. More specifically, we want to mark at most d vertices and to transform each layer into a cluster graph using at most k edge additions or deletions per layer so that, if we remove the marked vertices, we obtain the same cluster graph in all layers. In Temporal Cluster Editing we receive a sequence of layers and we want to transform each layer into a cluster graph so that consecutive layers differ only slightly. That is, we want to transform each layer into a cluster graph with at most k edge additions or deletions and to mark a distinct set of d vertices in each layer so that each two consecutive layers are the same after removing the vertices marked in the first of the two layers. We study the combinatorial structure of the two problems via their parameterized complexity with respect to the parameters d and k, among others. Despite the similar definition, the two problems behave quite differently: In particular, Multi-Layer Cluster Editing is fixed-parameter tractable with running time kO(k+d)sO(1) for inputs of size s, whereas Temporal Cluster Editing is W[1]-hard with respect to k even if d = 3.
AB - Motivated by the recent rapid growth of research for algorithms to cluster multi-layer and temporal graphs, we study extensions of the classical Cluster Editing problem. In Multi-Layer Cluster Editing we receive a set of graphs on the same vertex set, called layers and aim to transform all layers into cluster graphs (disjoint unions of cliques) that differ only slightly. More specifically, we want to mark at most d vertices and to transform each layer into a cluster graph using at most k edge additions or deletions per layer so that, if we remove the marked vertices, we obtain the same cluster graph in all layers. In Temporal Cluster Editing we receive a sequence of layers and we want to transform each layer into a cluster graph so that consecutive layers differ only slightly. That is, we want to transform each layer into a cluster graph with at most k edge additions or deletions and to mark a distinct set of d vertices in each layer so that each two consecutive layers are the same after removing the vertices marked in the first of the two layers. We study the combinatorial structure of the two problems via their parameterized complexity with respect to the parameters d and k, among others. Despite the similar definition, the two problems behave quite differently: In particular, Multi-Layer Cluster Editing is fixed-parameter tractable with running time kO(k+d)sO(1) for inputs of size s, whereas Temporal Cluster Editing is W[1]-hard with respect to k even if d = 3.
KW - Cluster Editing
KW - Fixed-Parameter Algorithms
KW - Multi-Layer Graphs
KW - Parameterized Complexity
KW - Polynomial Kernels
KW - Temporal Graphs
UR - https://www.scopus.com/pages/publications/85063695309
U2 - 10.4230/LIPIcs.ISAAC.2018.24
DO - 10.4230/LIPIcs.ISAAC.2018.24
M3 - Conference contribution
AN - SCOPUS:85063695309
T3 - Leibniz International Proceedings in Informatics, LIPIcs
SP - 24:1-24:13
BT - 29th International Symposium on Algorithms and Computation, ISAAC 2018
A2 - Lee, Der-Tsai
A2 - Liao, Chung-Shou
A2 - Hsu, Wen-Lian
PB - Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
T2 - 29th International Symposium on Algorithms and Computation, ISAAC 2018
Y2 - 16 December 2018 through 19 December 2018
ER -