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: "node expansions and cuts in gromov hyperbolic graphs"
  Abstract: Gromov-hyperbolic graphs (or, hyperbolic graphs for short) are a non-trivial interesting classes of "non-expander" graphs. Originally conceived by Gromov in 1987 in a different context while studying fundamental groups of a Riemann surface, the hyperbolicity measure for graphs has recently been a quite popular measure in the network science community in quantifying "curvature" and "closeness to a tree topology" for a given network, and many real-world networks have been empirically observed to be hyperbolic. #R##N#In this paper, we provide constructive non-trivial bounds on node expansions and cut-sizes for hyperbolic graphs, and show that witnesses for such non-expansion or cut-size can in fact be computed efficiently in polynomial time. We also provide some algorithmic consequences of these bounds and their related proof techniques for a few problems related to cuts and paths for hyperbolic graphs, such as the existence of a large family of s-t cuts with small number of cut-edges when s and t are at least logarithmically far apart, efficient approximation of hitting sets of size-constrained cuts, and a polynomial-time solution for a type of small-set expansion problem originally proposed by Arora, Barak and Steurer.

Connected through hyperedge HE-1 (induced by source paper "obstructions to a small hyperbolicity in helly graphs"):
  with members:
    - "fast approximation algorithms for p centres in large delta hyperbolic graphs"
    - "core congestion is inherent in hyperbolic networks"
    - "polynomial bounds for the grid minor theorem"
    - "on the hyperbolicity of small world and tree like random graphs"
    - "euclidean versus hyperbolic congestion in idealized versus experimental networks"

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)