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: "temporal reachability graphs"
  Abstract: While a natural fit for modeling and understanding mobile networks, time-varying graphs remain poorly understood. Indeed, many of the usual concepts of static graphs have no obvious counterpart in time-varying ones. In this paper, we introduce the notion of temporal reachability graphs. A (tau,delta)-reachability graph} is a time-varying directed graph derived from an existing connectivity graph. An edge exists from one node to another in the reachability graph at time t if there exists a journey (i.e., a spatiotemporal path) in the connectivity graph from the first node to the second, leaving after t, with a positive edge traversal time tau, and arriving within a maximum delay delta. We make three contributions. First, we develop the theoretical framework around temporal reachability graphs. Second, we harness our theoretical findings to propose an algorithm for their efficient computation. Finally, we demonstrate the analytic power of the temporal reachability graph concept by applying it to synthetic and real-life datasets. On top of defining clear upper bounds on communication capabilities, reachability graphs highlight asymmetric communication opportunities and offloading potential.

Connected through hyperedge HE-1 (induced by source paper "degree based outlier detection within ip traffic modelled as a link stream"):
  with members:
    - "non altering time scales for aggregation of dynamic networks into series of graphs"
    - "stream graphs and link streams for the modeling of interactions over time"
    - "discovering patterns of interest in ip traffic using cliques in bipartite link streams"
    - "an algebraic approach to temporal network analysis based on temporal quantities"
    - "a unifying model for representing time varying graphs"
    - "network traffic anomaly detection"
    - "graph based anomaly detection and description a survey"
    - "netsimile a scalable approach to size independent network similarity"

Connected through hyperedge HE-2 (induced by source paper "counting causal paths in big times series data on networks"):
  with members:
    - "motifs in temporal networks"
    - "when is a network a network multi order graphical model selection in pathways and temporal networks"
    - "node2vec scalable feature learning for networks"
    - "representing higher order dependencies in networks"

Connected through hyperedge HE-3 (induced by source paper "local distributed algorithms in highly dynamic networks"):
  with members:
    - "simple dynamic algorithms for maximal independent set and other problems"
    - "fully dynamic maximal independent set with sublinear update time"
    - "improved algorithms for fully dynamic maximal independent set"
    - "the cost of global broadcast in dynamic radio networks"
    - "information spreading in dynamic networks under oblivious adversaries"
    - "optimal dynamic distributed mis"
    - "enabling minimal dominating set in highly dynamic distributed systems"
    - "an improved distributed algorithm for maximal independent set"

Connected through hyperedge HE-4 (induced by source paper "finding structure in dynamic networks"):
  with members:
    - "the many faces of graph dynamics"
    - "enumerating maximal cliques in link streams with durations"
    - "the computational complexity of finding separators in temporal graphs"
    - "on the treewidth of dynamic graphs"

Connected through hyperedge HE-5 (induced by source paper "stream graphs and link streams for the modeling of interactions over time"):
  with members:
    - "degree based outlier detection within ip traffic modelled as a link stream"
    - "non altering time scales for aggregation of dynamic networks into series of graphs"
    - "movie rating prediction using content based and link stream features"
    - "motifs in temporal networks"
    - "discovering patterns of interest in ip traffic using cliques in bipartite link streams"
    - "time series analysis of temporal networks"
    - "graphprints towards a graph analytic method for network anomaly detection"
    - "semirings for temporal network analysis"

Connected through hyperedge HE-6 (induced by source paper "efficiently testing t interval connectivity in dynamic graphs"):
  with members:
    - "self stabilizing robots in highly dynamic environments"
    - "the next 700 impossibility results in time varying graphs"
    - "dmvp foremost waypoint coverage of time varying graphs"
    - "testing temporal connectivity in sparse dynamic graphs"
    - "shortest fastest and foremost broadcast in dynamic networks"
    - "characterizing topological assumptions of distributed algorithms in dynamic networks"
    - "time varying graphs and dynamic networks"

Connected through hyperedge HE-7 (induced by source paper "enabling minimal dominating set in highly dynamic distributed systems"):
  with members:
    - "the next 700 impossibility results in time varying graphs"
    - "shortest fastest and foremost broadcast in dynamic networks"
    - "characterizing topological assumptions of distributed algorithms in dynamic networks"
    - "on the feasibility of maintenance algorithms in dynamic graphs"
    - "time varying graphs and dynamic networks"

Connected through hyperedge HE-8 (induced by source paper "survivability in time varying networks"):
  with members:
    - "millimeter wave cellular wireless networks potentials and challenges"
    - "time varying graphs and dynamic 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.NI(Networking and Internet Architecture)