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: "light spanners in bounded pathwidth graphs"
  Abstract: Given an edge-weighted graph G and e>0, a (1+e)-spanner is a spanning subgraph G′ whose shortest path distances approximate those of G within a factor of 1+e. For G from certain graph families (such as bounded genus graphs and apex graphs), we know that light spanners exist. That is, we can compute a (1+e)-spanner G′ with total edge weight at most a constant times the weight of a minimum spanning tree. This constant may depend on e and the graph family, but not on the particular graph G nor on the edge weighting. The existence of light spanners is essential in the design of approximation schemes for the metric TSP (the traveling salesman problem) and similar graph-metric problems.#R##N##R##N#In this paper we make some progress towards the conjecture that light spanners exist for every minor-closed graph family: we show that light spanners exist for graphs with bounded pathwidth, and they are computed by a greedy algorithm. We do this via the intermediate construction of light monotone spanning trees in such graphs.

Connected through hyperedge HE-1 (induced by source paper "minor free graphs have light spanners"):
  with members:
    - "light spanners for bounded treewidth graphs imply light spanners for h minor free graphs"
    - "the greedy spanner is existentially optimal"
    - "polynomial time approximation schemes for subset connectivity problems in bounded genus graphs"

Connected through hyperedge HE-2 (induced by source paper "the greedy spanner is existentially optimal"):
  with members:
    - "on notions of distortion and an almost minimum spanning tree with constant average distortion"
    - "a light metric spanner"
    - "from hierarchical partitions to hierarchical covers optimal fault tolerant spanners for doubling metrics"
    - "fast constructions of light weight spanners for general graphs"
    - "fast construction of nets in low dimensional metrics and their applications"

Connected through hyperedge HE-3 (induced by source paper "a light metric spanner"):
  with members:
    - "the traveling salesman problem low dimensionality implies a polynomial time approximation scheme"
    - "light spanners for snowflake metrics"
    - "from hierarchical partitions to hierarchical covers optimal fault tolerant spanners for doubling metrics"
    - "optimal euclidean spanners really short thin and lanky"
    - "efficient regression in metric spaces via approximate lipschitz extension"
    - "shallow low and light trees and tight lower bounds for euclidean spanners"
    - "fast construction of nets in low dimensional metrics and their applications"

Connected through hyperedge HE-4 (induced by source paper "light spanners for snowflake metrics"):
  with members:
    - "the traveling salesman problem low dimensionality implies a polynomial time approximation scheme"
    - "from hierarchical partitions to hierarchical covers optimal fault tolerant spanners for doubling metrics"
    - "optimal euclidean spanners really short thin and lanky"
    - "an optimal time construction of euclidean sparse spanners with tiny diameter"
    - "shallow low and light trees and tight lower bounds for euclidean spanners"
    - "fast construction of nets in low dimensional metrics and their applications"

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)