human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "greedy routing and the algorithmic small world phenomenom"):
  Abstract: The algorithmic small-world phenomenon, empirically established by Milgram's letter forwarding experiments from the 60s, was theoretically explained by Kleinberg in 2000. However, from today's perspective his model has several severe shortcomings that limit the applicability to real-world networks. In order to give a more convincing explanation of the algorithmic small-world phenomenon, we study decentralized greedy routing in a more flexible random graph model (geometric inhomogeneous random graphs) which overcomes all previous shortcomings. Apart from exhibiting good properties in theory, it has also been extensively experimentally validated that this model reasonably captures real-world networks. #R##N#In this model, the greedy routing protocol is purely distributed as each vertex only needs to know information about its direct neighbors. We prove that it succeeds with constant probability, and in case of success almost surely finds an almost shortest path of length {\theta}(loglog n), where our bound is tight including the leading constant. Moreover, we study natural local patching methods which augment greedy routing by backtracking and which do not require any global knowledge. We show that such methods can ensure success probability 1 in an asymptotically tight number of steps. #R##N#These results also address the question of Krioukov et al. whether there are efficient local routing protocols for the internet graph. There were promising experimental studies, but the question remained unsolved theoretically. Our results give for the first time a rigorous and analytical affirmative answer.

Includes members:
  Member "average distance in a general class of scale free networks with underlying geometry":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "rumours spread slowly in a small world spatial network")
  Member "an experimental investigation of hyperbolic routing with a smart forwarding plane in ndn":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "link persistence and conditional distances in multiplex networks")
  Member "network mapping by replaying hyperbolic growth":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "social centralization and semantic collapse hyperbolic embeddings of networks and text")
  Member "geometric inhomogeneous random graphs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "recent advances in scalable network generation")
  Member "on the diameter of hyperbolic random graphs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "recent advances in scalable network generation")
  Member "four degrees of separation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "diffusion improves graph learning")
  Member "sustaining the internet with hyperbolic mapping":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "hyperkg hyperbolic knowledge graph embeddings for knowledge base completion")
  Member "networks become navigable as nodes move and forget":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "navigability is a robust property")

Question: Please tell me which class the source paper 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)