human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "adapting the bron kerbosch algorithm for enumerating maximal cliques in temporal graphs"
  Abstract: Dynamics of interactions play an increasingly important role in the analysis of complex networks. A modeling framework to capture this are temporal graphs which consist of a set of vertices (entities in the network) and a set of time-stamped binary interactions between the vertices. We focus on enumerating delta-cliques, an extension of the concept of cliques to temporal graphs: for a given time period delta, a delta-clique in a temporal graph is a set of vertices and a time interval such that all vertices interact with each other at least after every delta time steps within the time interval. Viard, Latapy, and Magnien [ASONAM 2015, TCS 2016] proposed a greedy algorithm for enumerating all maximal delta-cliques in temporal graphs. In contrast to this approach, we adapt the Bron-Kerbosch algorithm - an efficient, recursive backtracking algorithm which enumerates all maximal cliques in static graphs - to the temporal setting. We obtain encouraging results both in theory (concerning worst-case running time analysis based on the parameter "delta-slice degeneracy" of the underlying graph) as well as in practice with experiments on real-world data. The latter culminates in an improvement for most interesting delte-values concerning running time in comparison with the algorithm of Viard, Latapy, and Magnien.

Connected through hyperedge HE-1 (induced by source paper "computing maximum matchings in temporal graphs"):
  with members:
    - "temporal matching"
    - "how fast can we reach a target vertex in stochastic temporal graphs"
    - "fixed parameter algorithms for maximum profit facility location under matroid constraints"
    - "tight competitive ratios of classic matching algorithms in the fully online model"
    - "temporal vertex cover with a sliding time window"
    - "how to match when all vertices arrive online"
    - "sliding window temporal graph coloring"
    - "efficient and adaptive parameterized algorithms on modular decompositions"

Connected through hyperedge HE-2 (induced by source paper "how fast can we reach a target vertex in stochastic temporal graphs"):
  with members:
    - "temporal vertex cover with a sliding time window"
    - "deleting edges to restrict the size of an epidemic in temporal networks"
    - "sliding window temporal graph coloring"
    - "cover time in edge uniform stochastically evolving graphs"
    - "computing maximal cliques in link streams"
    - "temporal network optimization subject to connectivity constraints"
    - "on temporal graph exploration"
    - "dmvp foremost waypoint coverage of time varying graphs"

Connected through hyperedge HE-3 (induced by source paper "enumerating isolated cliques in temporal networks"):
  with members:
    - "community discovery in dynamic networks a survey"
    - "listing all maximal k plexes in temporal graphs"
    - "the parameterized complexity of finding secluded solutions to some classical optimization problems on graphs"
    - "enumerating maximal cliques in link streams with durations"
    - "stream graphs and link streams for the modeling of interactions over time"
    - "an introduction to temporal graphs an algorithmic perspective"
    - "computing maximal cliques in link streams"
    - "parameterized complexity of secluded connectivity problems"

Connected through hyperedge HE-4 (induced by source paper "temporal vertex cover with a sliding time window"):
  with members:
    - "temporal matching"
    - "how fast can we reach a target vertex in stochastic temporal graphs"
    - "the temporal explorer who returns to the base"
    - "sliding window temporal graph coloring"
    - "on problems as hard as cnf sat"
    - "computing maximal cliques in link streams"
    - "temporal network optimization subject to connectivity constraints"
    - "on temporal graph exploration"

Connected through hyperedge HE-5 (induced by source paper "listing all maximal k plexes in temporal graphs"):
  with members:
    - "computing maximum matchings in temporal graphs"
    - "temporal vertex cover with a sliding time window"
    - "sliding window temporal graph coloring"
    - "enumerating maximal cliques in link streams with durations"
    - "cluster editing for multi layer and temporal graphs"
    - "stream graphs and link streams for the modeling of interactions over time"
    - "the complexity of finding small separators in temporal graphs"
    - "enumerating maximal cliques in temporal graphs"

Connected through hyperedge HE-6 (induced by source paper "sliding window temporal graph coloring"):
  with members:
    - "deleting edges to restrict the size of an epidemic in temporal networks"
    - "temporal graph classes a view through temporal separators"
    - "listing all maximal k plexes in temporal graphs"
    - "stream graphs and link streams for the modeling of interactions over time"
    - "the complexity of finding small separators in temporal graphs"
    - "an introduction to temporal graphs an algorithmic perspective"
    - "computing maximal cliques in link streams"
    - "on temporal graph exploration"

Connected through hyperedge HE-7 (induced by source paper "the temporal explorer who returns to the base"):
  with members:
    - "on exploring temporal graphs of small pathwidth"
    - "temporal vertex cover with a sliding time window"
    - "computing maximal cliques in link streams"
    - "temporal network optimization subject to connectivity constraints"
    - "on temporal graph exploration"
    - "dmvp foremost waypoint coverage of time varying graphs"
    - "time varying graphs and dynamic networks"
    - "exploration of periodically varying graphs"

Connected through hyperedge HE-8 (induced by source paper "changing times to minimise reachability in temporal graphs"):
  with members:
    - "deleting edges to restrict the size of an epidemic in temporal networks"
    - "the computational complexity of finding separators in temporal graphs"
    - "survivability in time varying networks"
    - "deleting edges to restrict the size of an epidemic a new application for treewidth"
    - "an introduction to temporal graphs an algorithmic perspective"
    - "temporal network optimization subject to connectivity constraints"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.DS(Data Structures and Algorithms)