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 data reduction for dominating set"
  Abstract: Dealing with the NP-complete Dominating Set problem on undirected graphs, we demonstrate the power of data reduction by preprocessing from a theoretical as well as a practical side. In particular, we prove that Dominating Set restricted to planar graphs has a so-called problem kernel of linear size, achieved by two simple and easy to implement reduction rules. Moreover, having implemented our reduction rules, first experiments indicate the impressive practical potential of these rules. Thus, this work seems to open up a new and prospective way how to cope with one of the most important problems in graph theory and combinatorial optimization.

Connected through hyperedge HE-1 (induced by source paper "a general kernelization technique for domination and independence problems in sparse classes"):
  with members:
    - "kernelization and approximation of distance r independent sets on nowhere dense graphs"
    - "the generalised colouring numbers on classes of bounded expansion"
    - "characterising bounded expansion by neighbourhood complexity"
    - "polynomial kernels and wideness properties of nowhere dense graph classes"
    - "bidimensionality and kernels"
    - "kernels for connected dominating set on graphs with excluded topological subgraphs"

Connected through hyperedge HE-2 (induced by source paper "domination above r independence does sparseness help"):
  with members:
    - "neighborhood complexity and kernelization for nowhere dense classes of graphs"
    - "kernelization and sparseness the case of dominating set"
    - "faster parameterized algorithms using linear programming"
    - "testing first order properties for subclasses of sparse graphs"
    - "all ternary permutation constraint satisfaction problems parameterized above average have kernels with quadratic numbers of variables"
    - "vertex cover problem parameterized above and below tight bounds"
    - "solving max r sat above a tight lower bound"
    - "linear time algorithms for finding a dominating set of fixed size in degenerated graphs"

Connected through hyperedge HE-3 (induced by source paper "empirical evaluation of approximation algorithms for generalized graph coloring and uniform quasi wideness"):
  with members:
    - "exactly solving the maximum weight independent set problem on large real world graphs"
    - "experimental evaluation of kernelization algorithms to dominating set"
    - "polynomial bounds for centered colorings on proper minor closed graph classes"
    - "kernelization and approximation of distance r independent sets on nowhere dense graphs"
    - "distributed domination on graph classes of bounded expansion"
    - "reconfiguration on nowhere dense graph classes"
    - "positive instance driven dynamic programming for treewidth"
    - "experimental evaluation of counting subgraph isomorphisms in classes of bounded expansion"

Connected through hyperedge HE-4 (induced by source paper "lossy kernels for connected dominating set on sparse graphs"):
  with members:
    - "from gap eth to fpt inapproximability clique dominating set and more"
    - "on the number of types in sparse graphs"
    - "the generalised colouring numbers on classes of bounded expansion"
    - "characterising bounded expansion by neighbourhood complexity"
    - "polynomial kernels and wideness properties of nowhere dense graph classes"
    - "bidimensionality and kernels"
    - "neighborhood complexity and kernelization for nowhere dense classes of graphs"
    - "approximation algorithms for polynomial expansion and low density graphs"

Connected through hyperedge HE-5 (induced by source paper "conflict free coloring of planar graphs"):
  with members:
    - "minimum weight triangulation is np hard"

Connected through hyperedge HE-6 (induced by source paper "characterising bounded expansion by neighbourhood complexity"):
  with members:
    - "bidimensionality and kernels"
    - "structural sparsity of complex networks bounded expansion in random models and real world graphs"
    - "kernelization and sparseness the case of dominating set"
    - "kernelization using structural parameters on sparse graph classes"
    - "deciding first order properties of nowhere dense graphs"
    - "kernels for connected dominating set on graphs with excluded topological subgraphs"
    - "linear kernels and single exponential algorithms via protrusion decompositions"
    - "structure theorem and isomorphism test for graphs with excluded topological subgraphs"

Connected through hyperedge HE-7 (induced by source paper "explicit linear kernels for packing problems"):
  with members:
    - "bidimensionality and kernels"
    - "kernelization algorithms for packing problems allowing overlaps"
    - "scattered packings of cycles"
    - "induced packings of cycles"
    - "large treewidth graph decompositions and applications"
    - "explicit linear kernels via dynamic programming"
    - "polynomial bounds for the grid minor theorem"
    - "linear kernels and single exponential algorithms via protrusion decompositions"

Connected through hyperedge HE-8 (induced by source paper "bidimensionality and kernels"):
  with members:
    - "improved bounds for the excluded grid theorem"
    - "linear kernels for edge deletion problems to immersion closed graph classes"
    - "neighborhood complexity and kernelization for nowhere dense classes of graphs"
    - "kernelization and sparseness the case of dominating set"
    - "explicit linear kernels via dynamic programming"
    - "bidimensionality of geometric intersection graphs"
    - "polynomial bounds for the grid minor theorem"
    - "kernels for connected dominating set on graphs with excluded topological subgraphs"

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)