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: "changing times to minimise reachability in temporal graphs"
  Abstract: Temporal graphs (in which edges are active only at specified time steps) are an increasingly important and popular model for a wide variety of natural and social phenomena. We propose a new extension of classical graph modification problems into the temporal setting, and describe several variations on a modification problem in which we assign times to edges so as to maximise or minimise reachability sets within a temporal graph. #R##N#We give an assortment of complexity results on these problems, showing that they are hard under a variety of restrictions. In particular, if edges can be grouped into classes that must be assigned the same time, then our problem is hard even on directed acyclic graphs when both the reachability target and the classes of edges are of constant size, as well as on an extremely restrictive class of trees. We further show that one version of the problem is W[1]-hard when parameterised by the vertex cover number of the instance graph. #R##N#In the case that each edge is active at a unique timestep, we identify some very restricted cases in which the problem is solvable in polynomial time; however, list versions of both problems (each edge may only be assigned times from a specified lists) remain NP-complete in this setting even if the graph is of bounded degree and the reachability target is a constant.

Connected through hyperedge HE-1 (induced by source paper "the computational complexity of finding temporal paths under waiting time constraints"):
  with members:
    - "an adaptive version of brandes algorithm for betweenness centrality"
    - "efficient computation of optimal temporal walks under waiting time constraints"
    - "how fast can we reach a target vertex in stochastic temporal graphs"
    - "temporal cliques admit sparse spanners"
    - "fixed parameter algorithms for maximum profit facility location under matroid constraints"
    - "the temporal explorer who returns to the base"
    - "deleting edges to restrict the size of an epidemic in temporal networks"
    - "stream graphs and link streams for the modeling of interactions over time"

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.CC(Computational Complexity)