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: "networks become navigable as nodes move and forget"
  Abstract: We propose a dynamical process for network evolution, aiming at explaining the emergence of the small world phenomenon, i.e., the statistical observation that any pair of individuals are linked by a short chain of acquaintances computable by a simple decentralized routing algorithm, known as greedy routing. Previously proposed dynamical processes enabled to demonstrate experimentally (by simulations) that the small world phenomenon can emerge from local dynamics. However, the analysis of greedy routing using the probability distributions arising from these dynamics is quite complex because of mutual dependencies. In contrast, our process enables complete formal analysis. It is based on the combination of two simple processes: a random walk process, and an harmonic forgetting process. Both processes reflect natural behaviors of the individuals, viewed as nodes in the network of inter-individual acquaintances. We prove that, in k-dimensional lattices, the combination of these two processes generates long-range links mutually independently distributed as a k-harmonic distribution. We analyze the performances of greedy routing at the stationary regime of our process, and prove that the expected number of steps for routing from any source to any target in any multidimensional lattice is a polylogarithmic function of the distance between the two nodes in the lattice. Up to our knowledge, these results are the first formal proof that navigability in small worlds can emerge from a dynamical process for network evolution. Our dynamical process can find practical applications to the design of spatial gossip and resource location protocols.

Connected through hyperedge HE-1 (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"
    - "on the diameter of hyperbolic random graphs"
    - "four degrees of separation"
    - "sustaining the internet with hyperbolic mapping"
    - "on compact routing for the internet"

Connected through hyperedge HE-2 (induced by source paper "navigability is a robust property"):
  with members:
    - "product measure approximation of symmetric graph properties"
    - "fault tolerant routing in peer to peer systems"

Connected through hyperedge HE-3 (induced by source paper "a game theoretic model for the formation of navigable small world networks the balance between distance and reciprocity"):
  with members:
    - "evolution of social attribute networks measurements modeling and implications using google"
    - "uncovering social network sybils in the wild"
    - "distance is not dead social interaction and geographical distance in the internet era"
    - "the evolution of navigable small world networks"

Connected through hyperedge HE-4 (induced by source paper "nextbestonce achieving polylog routing despite non greedy embeddings"):
  with members:
    - "x vine secure and pseudonymous routing using social networks"

Connected through hyperedge HE-5 (induced by source paper "adaptive dynamics of realistic small world networks"):
  with members:
    - "the evolution of navigable small world 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.DS(Data Structures and Algorithms)