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: "information spreading in dynamic graphs"
  Abstract: We present a general approach to study the flooding time (a measure of how fast information spreads) in dynamic graphs (graphs whose topology changes with time according to a random process). #R##N#We consider arbitrary converging Markovian dynamic graph process, that is, processes in which the topology of the graph at time $t$ depends only on its topology at time $t-1$ and which have a unique stationary distribution. The most well studied models of dynamic graphs are all Markovian and converging. #R##N#Under general conditions, we bound the flooding time in terms of the mixing time of the dynamic graph process. We recover, as special cases of our result, bounds on the flooding time for the \emph{random trip} model and the \emph{random path} models; previous analysis techniques provided bounds only in restricted settings for such models. Our result also provides the first bound for the \emph{random waypoint} model (which is tight for certain ranges of parameters) whose analysis had been an important open question.

Connected through hyperedge HE-1 (induced by source paper "relative hausdorff distance for network analysis"):
  with members:
    - "multi centrality graph spectral decompositions and their application to cyber intrusion detection"
    - "catching the head tail and everything in between a streaming algorithm for the degree distribution"
    - "computing the gromov hausdorff distance for metric trees"
    - "graph based anomaly detection and description a survey"
    - "quantification and comparison of degree distributions in complex networks"
    - "a tutorial on spectral clustering"

Connected through hyperedge HE-2 (induced by source paper "improved bounds on information dissemination by manhattan random waypoint model"):
  with members:
    - "tight bounds on information dissemination in sparse mobile networks"
    - "inferring networks of diffusion and influence"
    - "fast flooding over manhattan"
    - "modelling mobility a discrete revolution"

Connected through hyperedge HE-3 (induced by source paper "capacity and delay scaling for broadcast transmission in highly mobile wireless networks"):
  with members:
    - "survey of important issues in uav communication networks"
    - "information spreading in stationary markovian evolving graphs"

Connected through hyperedge HE-4 (induced by source paper "live exploration of dynamic rings"):
  with members:
    - "an introduction to temporal graphs an algorithmic perspective"
    - "on temporal graph exploration"
    - "naming and counting in anonymous unknown dynamic networks"
    - "lower bounds on information dissemination in dynamic networks"
    - "agreement in directed dynamic networks"
    - "shortest fastest and foremost broadcast in dynamic networks"
    - "information spreading in stationary markovian evolving graphs"
    - "time varying graphs and dynamic networks"

Connected through hyperedge HE-5 (induced by source paper "smoothed analysis of dynamic networks"):
  with members:
    - "lower bounds for structuring unreliable radio networks"
    - "fast distributed computation in dynamic networks via random walks"
    - "faster information dissemination in dynamic networks via network coding"
    - "smoothed analysis of algorithms why the simplex algorithm usually takes polynomial time"

Connected through hyperedge HE-6 (induced by source paper "global information sharing under network dynamics"):
  with members:
    - "information spreading in dynamic networks"
    - "faster information dissemination in dynamic networks via network coding"
    - "order optimal information spreading using algebraic gossip"
    - "time varying graphs and dynamic networks"
    - "analyzing network coding gossip made easy"
    - "optimal gossip based aggregate computation"

Connected through hyperedge HE-7 (induced by source paper "on the role of mobility for multimessage gossip"):
  with members:
    - "tight bounds on information dissemination in sparse mobile networks"
    - "information spreading in stationary markovian evolving graphs"
    - "analyzing network coding gossip made easy"
    - "distributed averaging via lifted markov chains"
    - "the impact of mobility on gossip algorithms"
    - "gossiping with multiple messages"
    - "fast distributed algorithms for computing separable functions"

Connected through hyperedge HE-8 (induced by source paper "lower bounds on information dissemination in dynamic networks"):
  with members:
    - "information spreading in dynamic networks"
    - "one packet suffices highly efficient packetized network coding with finite memory"
    - "information spreading in stationary markovian evolving graphs"
    - "faster information dissemination in dynamic networks via network coding"
    - "optimal gradient clock synchronization in dynamic networks"
    - "analyzing network coding gossip made easy"

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)