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: "improved approximations for cubic and cubic bipartite tsp"
  Abstract: We show improved approximation guarantees for the traveling salesman problem on cubic graphs, and cubic bipartite graphs. For cubic bipartite graphs with n nodes, we improve on recent results of Karp and Ravi (2014) by giving a simple "local improvement" algorithm that finds a tour of length at most 5/4 n - 2. For 2-connected cubic graphs, we show that the techniques of Moemke and Svensson (2011) can be combined with the techniques of Correa, Larre and Soto (2012), to obtain a tour of length at most (4/3-1/8754)n.

Connected through hyperedge HE-1 (induced by source paper "a 9 7 approximation algorithm for graphic tsp in cubic bipartite graphs"):
  with members:
    - "an improved analysis of the m omke svensson algorithm for graph tsp on subquartic graphs"
    - "tsp tours in cubic graphs beyond 4 3"
    - "shorter tours by nicer ears 7 5 approximation for graphic tsp 3 2 for the path version and 4 3 for two edge connected subgraphs"
    - "approximating graphic tsp by matchings"
    - "a 4 3 approximation for tsp on cubic 3 edge connected graphs"
    - "the traveling salesman problem on cubic and subcubic graphs"

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)