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: "a 1 varepsilon embedding of low highway dimension graphs into bounded treewidth graphs"
  Abstract: Graphs with bounded highway dimension were introduced by Abraham et al. [Proceedings of SODA 2010, pp. 782--793] as a model of transportation networks. We show that any such graph can be embedded i...

Connected through hyperedge HE-1 (induced by source paper "travelling on graphs with small highway dimension"):
  with members:
    - "hierarchy of transportation network parameters and hardness results"
    - "the parameterized hardness of the k center problem in transportation networks"
    - "structural parameters tight bounds and approximation for k r center"
    - "beyond highway dimension small distance labels using tree skeletons"
    - "solving generalized maximum weight connected subgraph problem for network enrichment analysis"
    - "fixed parameter approximations for k center problems in low highway dimension graphs"
    - "the traveling salesman problem low dimensionality implies a polynomial time approximation scheme"
    - "efficient activity detection in untrimmed video with max subgraph search"

Connected through hyperedge HE-2 (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"
    - "polynomial time approximation schemes for k center and bounded capacity vehicle routing in metrics with bounded highway dimension"
    - "a quasi polynomial time approximation scheme for euclidean capacitated vehicle routing"

Connected through hyperedge HE-3 (induced by source paper "hierarchy of transportation network parameters and hardness results"):
  with members:
    - "the parameterized hardness of the k center problem in transportation networks"
    - "beyond highway dimension small distance labels using tree skeletons"

Connected through hyperedge HE-4 (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"
    - "structural parameters tight bounds and approximation for k r center"
    - "polynomial time approximation schemes for k center and bounded capacity vehicle routing in metrics with bounded highway dimension"
    - "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-5 (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"
    - "structural parameters tight bounds and approximation for k r center"
    - "polynomial time approximation schemes for k center and bounded capacity vehicle routing in metrics with bounded highway dimension"
    - "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)