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: "polynomial time approximation schemes for k center and bounded capacity vehicle routing in metrics with bounded highway dimension"
  Abstract: The concept of bounded highway dimension was developed to capture observed properties of the metrics of road networks. We show that a graph with bounded highway dimension, for any vertex, can be embedded into a a graph of bounded treewidth in such a way that the distance between $u$ and $v$ is preserved up to an additive error of $\epsilon$ times the distance from $u$ or $v$ to the selected vertex. We show that this theorem yields a PTAS for Bounded-Capacity Vehicle Routing in graphs of bounded highway dimension. In this problem, the input specifies a depot and a set of clients, each with a location and demand; the output is a set of depot-to-depot tours, where each client is visited by some tour and each tour covers at most $Q$ units of client demand. Our PTAS can be extended to handle penalties for unvisited clients. #R##N#We extend this embedding result to handle a set $S$ of distinguished vertices. The treewidth depends on $|S|$, and the distance between $u$ and $v$ is preserved up to an additive error of $\epsilon$ times the distance from $u$ and $v$ to $S$. #R##N#This embedding result implies a PTAS for Multiple Depot Bounded-Capacity Vehicle Routing: the tours can go from one depot to another. The embedding result also implies that, for fixed $k$, there is a PTAS for $k$-Center in graphs of bounded highway dimension. In this problem, the goal is to minimize $d$ such that there exist $k$ vertices (the centers) such that every vertex is within distance $d$ of some center. Similarly, for fixed $k$, there is a PTAS for $k$-Median in graphs of bounded highway dimension. In this problem, the goal is to minimize the sum of distances to the $k$ centers.

Connected through hyperedge HE-1 (induced by source paper "a ptas for bounded capacity vehicle routing in planar graphs"):
  with members:
    - "a tight 4 3 approximation for capacitated vehicle routing in trees"
    - "a framework for vehicle routing approximation schemes in trees"
    - "a 1 varepsilon embedding of low highway dimension graphs into bounded treewidth graphs"
    - "a quasi polynomial time approximation scheme for euclidean capacitated vehicle routing"

Connected through hyperedge HE-2 (induced by source paper "the parameterized hardness of the k center problem in transportation networks"):
  with members:
    - "hierarchy of transportation network parameters and hardness results"
    - "a 1 varepsilon embedding of low highway dimension graphs into bounded treewidth graphs"
    - "structural parameters tight bounds and approximation for k r center"
    - "the limited blessing of low dimensionality when 1 1 d is the best possible exponent for d dimensional geometric problems"
    - "fixed parameter approximations for k center problems in low highway dimension graphs"
    - "optimal parameterized algorithms for planar facility location problems using voronoi diagrams"
    - "analytical approach to parallel repetition"
    - "improved approximation algorithms for budgeted node weighted steiner problems"

Connected through hyperedge HE-3 (induced by source paper "a tight 4 3 approximation for capacitated vehicle routing in trees"):
  with members:
    - "a quasi polynomial time approximation scheme for euclidean capacitated vehicle routing"

Connected through hyperedge HE-4 (induced by source paper "fixed parameter approximations for k center problems in low highway dimension graphs"):
  with members:
    - "the parameterized hardness of the k center problem in transportation networks"
    - "a 1 varepsilon embedding of low highway dimension graphs into bounded treewidth graphs"
    - "structural parameters tight bounds and approximation for k r center"
    - "beyond highway dimension small distance labels using tree skeletons"
    - "optimal parameterized algorithms for planar facility location problems using voronoi diagrams"
    - "parameterized approximation schemes using graph widths"

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)