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: "on the diameter of hyperbolic random graphs"
  Abstract: For understanding the structure of the resulting graphs and for analyzing the behavior of network algorithms, the next question is bounding the size of the diameter. The only known bound is $$\mathcal {O}\log n^{32/3-\beta 5-\beta }$$ Kiwi and Mitsche. ANALCO, pp. 26---39, 2015. We present two much simpler proofs for an improved upper bound of $$\mathcal {O}\log n^{2/3-\beta }$$ and a lower bound of $$\Omega \log n$$. If the average degree is bounded from above by some constant, we show that the latter bound is tight by proving an upper bound of $$\mathcal {O}\log n$$ for the diameter.

Connected through hyperedge HE-1 (induced by source paper "recent advances in scalable network generation"):
  with members:
    - "efficiently generating geometric inhomogeneous and hyperbolic random graphs"
    - "exploring randomly wired neural networks for image recognition"
    - "parallel weighted random sampling"
    - "linear work generation of r mat graphs"
    - "egbter capturing degree distribution clustering coefficients and community structure in a single random graph model"
    - "multiscale planar graph generation"
    - "parallel and i o efficient randomisation of massive networks using global curveball trades"
    - "efficient parallel random sampling vectorized cache efficient and online"

Connected through hyperedge HE-2 (induced by source paper "link persistence and conditional distances in multiplex networks"):
  with members:
    - "a dynamic network model with persistent links and node specific latent variables with an application to the interbank market"
    - "an experimental investigation of hyperbolic routing with a smart forwarding plane in ndn"
    - "network mapping by replaying hyperbolic growth"
    - "spreading processes in multilayer networks"
    - "network geometry inference using common neighbors"
    - "sustaining the internet with hyperbolic mapping"

Connected through hyperedge HE-3 (induced by source paper "updating dynamic random hyperbolic graphs in sublinear time"):
  with members:
    - "nearest neighbor searching under uncertainty ii"
    - "querying probabilistic neighborhoods in spatial data sets efficiently"
    - "generating massive complex networks with hyperbolic geometry faster in practice"
    - "generating scaled replicas of real world complex networks"
    - "sampling geometric inhomogeneous random graphs in linear time"
    - "geometric inhomogeneous random graphs"
    - "approximating betweenness centrality in fully dynamic networks"
    - "fast generation of complex networks with underlying hyperbolic geometry"

Connected through hyperedge HE-4 (induced by source paper "hyperbolic intersection graphs and quasi polynomial time"):
  with members:
    - "solving vertex cover in polynomial time on hyperbolic random graphs"
    - "a framework for eth tight algorithms and lower bounds in geometric intersection graphs"
    - "finding hitting and packing cycles in subexponential time on unit disk graphs"
    - "the limited blessing of low dimensionality when 1 1 d is the best possible exponent for d dimensional geometric problems"
    - "subexponential parameterized algorithms for graphs of polynomial growth"
    - "computing the gromov hyperbolicity of a discrete metric space"
    - "complexity dichotomy on partial grid recognition"

Connected through hyperedge HE-5 (induced by source paper "greedy routing and the algorithmic small world phenomenom"):
  with members:
    - "average distance in a general class of scale free networks with underlying geometry"
    - "an experimental investigation of hyperbolic routing with a smart forwarding plane in ndn"
    - "network mapping by replaying hyperbolic growth"
    - "geometric inhomogeneous random graphs"
    - "four degrees of separation"
    - "sustaining the internet with hyperbolic mapping"
    - "networks become navigable as nodes move and forget"
    - "on compact routing for the internet"

Connected through hyperedge HE-6 (induced by source paper "geometric inhomogeneous random graphs"):
  with members:
    - "average distance in a general class of scale free networks with underlying geometry"
    - "greedy routing and the algorithmic small world phenomenom"
    - "network mapping by replaying hyperbolic growth"
    - "fast generation of dynamic complex networks with underlying hyperbolic geometry"
    - "fast generation of complex networks with underlying hyperbolic geometry"
    - "sustaining the internet with hyperbolic mapping"

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.DM(Discrete Mathematics)