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: "the computational complexity of finding separators in temporal graphs"
  Abstract: Vertex separators, that is, vertex sets whose deletion disconnects two distinguished vertices in a graph, play a pivotal role in algorithmic graph theory. For instance, the concept of tree decompositions of graphs is tightly connected to the separator concept. For many realistic models of the real world, however, it is necessary to consider graphs whose edge set changes with time. More specifically, the edges are labeled with time stamps. In the literature, these graphs are referred to as temporal graphs, temporal networks, time-varying networks, edge-scheduled networks, etc. While there is an extensive literature on separators in "static" graphs, much less is known for the temporal setting. Building on previous work (e.g., Kempe et al. [STOC '00]), for the first time we systematically investigate the (parameterized) complexity of finding separators in temporal graphs. Doing so, we discover a rich landscape of computationally (fixed-parameter) tractable and intractable cases. In particular, we shed light on the so far seemingly overlooked fact that two frequently used models of temporal separation may lead to quite significant differences in terms of computational complexity. More specifically, considering paths in temporal graphs one may distinguish between strict paths (the time stamps along a path are strictly increasing) and non-strict paths (the time stamps along a path are monotonically non-decreasing). We observe that the corresponding strict case of temporal separators leads to several computationally much easier to handle cases than the non-strict case does.

Connected through hyperedge HE-1 (induced by source paper "on polynomial time combinatorial algorithms for maximum l bounded flow"):
  with members:
    - "a more fine grained complexity analysis of finding the most vital edges for undirected shortest paths"
    - "improved hardness for cut interdiction and firefighter problems"
    - "fractals for kernelization lower bounds with an application to length bounded cut problems"

Connected through hyperedge HE-2 (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"
    - "adapting the bron kerbosch algorithm for enumerating maximal cliques 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"

Connected through hyperedge HE-3 (induced by source paper "temporal graph classes a view through temporal separators"):
  with members:
    - "the complexity of finding small separators in temporal graphs"
    - "on the size and the approximability of minimum temporally connected subgraphs"
    - "steiner network problems on temporal graphs"
    - "an introduction to temporal graphs an algorithmic perspective"
    - "on temporal graph exploration"
    - "time varying graphs and dynamic networks"

Connected through hyperedge HE-4 (induced by source paper "finding structure in dynamic networks"):
  with members:
    - "the many faces of graph dynamics"
    - "enumerating maximal cliques in link streams with durations"
    - "temporal reachability graphs"
    - "on the treewidth of dynamic graphs"

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)