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: "euclidean versus hyperbolic congestion in idealized versus experimental networks"
  Abstract: Abstract This paper proposes a mathematical justification of the phenomenon of extreme congestion at a very limited number of nodes in very large networks. It is argued that this phenomenon occurs as a combination of the negative curvature property of the network together with minimum-length routing. More specifically, it is shown that in a large n-dimensional hyperbolic ball B of radius R viewed as a roughly similar model of a Gromov hyperbolic network, the proportion of traffic paths transiting through a small ball near the center is Θ(1), whereas in a Euclidean ball, the same proportion scales as Θ(1/R n−1). This discrepancy persists for the traffic load, which at the center of the hyperbolic ball scales as volume2(B), whereas the same traffic load scales as volume1+1/n (B) in the Euclidean ball. This provides a theoretical justification of the experimental exponent discrepancy observed by Narayan and Saniee between traffic loads in Gromov-hyperbolic networks from the Rocketfuel database and synthetic ...

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"
    - "node expansions and cuts in gromov hyperbolic graphs"
    - "polynomial bounds for the grid minor theorem"
    - "on the hyperbolicity of small world and tree like random graphs"

Connected through hyperedge HE-2 (induced by source paper "why did the shape of your network change on detecting network anomalies via non local curvatures"):
  with members:
    - "fast approximation and exact computation of negative curvature parameters of graphs"
    - "effect of gromov hyperbolicity parameter on cuts and expansions in graphs and some algorithmic implications"
    - "forman ricci flow for change detection in large dynamic data sets"
    - "computing the gromov hyperbolicity of a discrete metric space"

Connected through hyperedge HE-3 (induced by source paper "effect of gromov hyperbolicity parameter on cuts and expansions in graphs and some algorithmic implications"):
  with members:
    - "the complexity of approximating vertex expansion"
    - "computing the gromov hyperbolicity of a discrete metric space"
    - "reductions between expansion problems"

Connected through hyperedge HE-4 (induced by source paper "slimness of graphs"):
  with members:
    - "fast approximation and exact computation of negative curvature parameters of graphs"
    - "core congestion is inherent in hyperbolic networks"
    - "tree decompositions and social graphs"

Connected through hyperedge HE-5 (induced by source paper "core congestion is inherent in hyperbolic networks"):
  with members:
    - "on the hyperbolicity of small world and tree like random graphs"
    - "community structure in large networks natural cluster sizes and the absence of large well defined clusters"

Connected through hyperedge HE-6 (induced by source paper "ricci curvature of the internet topology"):
  with members:
    - "dimes let the internet measure itself"
    - "mapping the gnutella network properties of large scale peer to peer systems and implications for system design"

Connected through hyperedge HE-7 (induced by source paper "node expansions and cuts in gromov hyperbolic graphs"):
  with members:
    - "the complexity of approximating vertex expansion"
    - "computing the gromov hyperbolicity of a discrete metric space"

Connected through hyperedge HE-8 (induced by source paper "a geometric distance oracle for large real world graphs"):
  with members:
    - "fast exact shortest path distance queries on large networks by pruned landmark labeling"
    - "ramsey partitions and proximity data structures"

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.NI(Networking and Internet Architecture)