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: "the emergence of sparse spanners and greedy well separated pair decomposition"
  Abstract: A spanner graph on a set of points in ℝd provides shortest paths between any pair of points with lengths at most a constant factor of their Euclidean distance. A spanner with a sparse set of edges is thus a good candidate for network backbones, as in transportation networks and peer-to-peer network overlays. In this paper we investigate new models and aim to interpret why good spanners ‘emerge' in reality, when they are clearly built in pieces by agents with their own interests and the construction is not coordinated. Our main result is to show that the following algorithm generates a (1+e)-spanner with a linear number of edges. In our algorithm, the points build edges at an arbitrary order. A point p will only build an edge pq if there is no existing edge p′q′ with p′ and q′ at distances no more than $\frac{1}{4(1+1/\varepsilon)} \cdot |pq|$ from p, q respectively. Eventually when all points finish checking edges to all other points, the resulted collection of edges forms a sparse spanner as desired. As a side product, the spanner construction implies a greedy algorithm for constructing linear-size well-separated pair decompositions that may be of interest on its own.

Connected through hyperedge HE-1 (induced by source paper "diameter spanners eccentricity spanners and approximating extremal distances"):
  with members:
    - "towards tight approximation bounds for graph diameter and eccentricities"
    - "linear size distance preservers"
    - "the 4 3 additive spanner exponent is tight"
    - "experience based planning with sparse roadmap spanners"

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.CG(Computational Geometry)