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: "modelling mobility a discrete revolution"
  Abstract: We introduce a new approach to model and analyze \emph{Mobility}. It is fully based on discrete mathematics and yields a class of mobility models, called the \emph{Markov Trace} Model. This model can be seen as the discrete version of the \emph{Random Trip} Model including all variants of the \emph{Random Way-Point} Model \cite{L06}. #R##N#We derive fundamental properties and \emph{explicit} analytical formulas for the \emph{stationary distributions} yielded by the Markov Trace Model. Such results can be exploited to compute formulas and properties for concrete cases of the Markov Trace Model by just applying counting arguments. #R##N#We apply the above general results to the discrete version of the \emph{Manhattan Random Way-Point} over a square of bounded size. #R##N#We get formulas for the total stationary distribution and for two important \emph{conditional} ones: the agent spatial and destination distributions. Our method makes the analysis of complex mobile systems a feasible task. #R##N#As a further evidence of this important fact, we first model a complex vehicular-mobile system over a set of crossing streets. Several concrete issues are implemented such as parking zones, traffic lights, and variable vehicle speeds. By using a \emph{modular} version of the Markov Trace Model, we get explicit formulas for the stationary distributions yielded by this vehicular-mobile model as well.

Connected through hyperedge HE-1 (induced by source paper "improved bounds on information dissemination by manhattan random waypoint model"):
  with members:
    - "information spreading in dynamic graphs"
    - "tight bounds on information dissemination in sparse mobile networks"
    - "inferring networks of diffusion and influence"
    - "fast flooding over manhattan"

Connected through hyperedge HE-2 (induced by source paper "information spreading in dynamic graphs"):
  with members:
    - "tight bounds on information dissemination in sparse mobile networks"
    - "information spreading in stationary markovian evolving graphs"
    - "flooding time in opportunistic networks under power law and exponential inter contact times"
    - "performance of opportunistic epidemic routing on edge markovian dynamic graphs"
    - "fast flooding over manhattan"
    - "information propagation speed in mobile and delay tolerant networks"
    - "manets high mobility can make up for low transmission power"

Connected through hyperedge HE-3 (induced by source paper "on the treewidth of dynamic graphs"):
  with members:
    - "characterizing topological assumptions of distributed algorithms in dynamic networks"
    - "time varying graphs and dynamic networks"
    - "information propagation speed in mobile and delay tolerant networks"
    - "exploration of periodically varying graphs"
    - "the monadic second order logic of graphs xvi canonical graph decompositions"
    - "deciding first order properties of locally tree decomposable structures"

Connected through hyperedge HE-4 (induced by source paper "fast flooding over manhattan"):
  with members:
    - "information spreading in dynamic graphs"
    - "tight bounds on information dissemination in sparse mobile networks"
    - "information spreading in stationary markovian evolving graphs"
    - "information propagation speed in mobile and delay tolerant networks"
    - "manets high mobility can make up for low transmission power"
    - "swim a simple model to generate small mobile worlds"

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)