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 hyperbolicity of small world and tree like random graphs"
  Abstract: Hyperbolicity is a property of a graph that may be viewed as being a "soft" version of a tree, and recent empirical and theoretical work has suggested that many graphs arising in Internet and related data applications have hyperbolic properties. We consider Gromov's notion of \delta-hyperbolicity, and establish several results for small-world and tree-like random graph models. First, we study the hyperbolicity of Kleinberg small-world random graphs and show that the hyperbolicity of these random graphs is not significantly improved comparing to graph diameter even when it greatly improves decentralized navigation. Next we study a class of tree-like graphs called ringed trees that have constant hyperbolicity. We show that adding random links among the leaves similar to the small-world graph constructions may easily destroy the hyperbolicity of the graphs, except for a class of random edges added using an exponentially decaying probability function based on the ring distance among the leaves. #R##N#Our study provides one of the first significant analytical results on the hyperbolicity of a rich class of random graphs, which shed light on the relationship between hyperbolicity and navigability of random graphs, as well as on the sensitivity of hyperbolic {\delta} to noises in random graphs.

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"
    - "euclidean versus hyperbolic congestion in idealized versus experimental networks"

Connected through hyperedge HE-2 (induced by source paper "a geometric approach for real time monitoring of dynamic large scale graphs as level graphs illustrated"):
  with members:
    - "a survey among network operators on bgp prefix hijacking"
    - "a comprehensive survey of graph embedding problems techniques and applications"
    - "optimal approximate matrix product in terms of stable rank"

Connected through hyperedge HE-3 (induced by source paper "core congestion is inherent in hyperbolic networks"):
  with members:
    - "euclidean versus hyperbolic congestion in idealized versus experimental networks"
    - "community structure in large networks natural cluster sizes and the absence of large well defined clusters"

Connected through hyperedge HE-4 (induced by source paper "metric tree like structures in real life networks an empirical study"):
  with members:
    - "computing the gromov hyperbolicity of a discrete metric space"
    - "defining and evaluating network communities based on ground truth"
    - "community structure in large networks natural cluster sizes and the absence of large well defined clusters"
    - "dimes let the internet measure itself"

Connected through hyperedge HE-5 (induced by source paper "hyperbolicity degeneracy and expansion of random intersection graphs"):
  with members:
    - "connectivity in secure wireless sensor networks under transmission constraints"
    - "structural sparsity of complex networks bounded expansion in random models and real world graphs"
    - "on the strengths of connectivity and robustness in general random intersection 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.SI(Social and Information Networks)