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: "meta kernelization with structural parameters"
  Abstract: Meta-kernelization theorems are general results that provide polynomial kernels for large classes of parameterized problems. The known meta-kernelization theorems, in particular the results of Bodlaender et al. (FOCS'09) and of Fomin et al. (FOCS'10), apply to optimization problems parameterized by solution size. We present the first meta-kernelization theorems that use a structural parameters of the input and not the solution size. Let C be a graph class. We define the C-cover number of a graph to be a the smallest number of modules the vertex set can be partitioned into, such that each module induces a subgraph that belongs to the class C. We show that each graph problem that can be expressed in Monadic Second Order (MSO) logic has a polynomial kernel with a linear number of vertices when parameterized by the C-cover number for any fixed class C of bounded rank-width (or equivalently, of bounded clique-width, or bounded Boolean width). Many graph problems such as Independent Dominating Set, c-Coloring, and c-Domatic Number are covered by this meta-kernelization result. Our second result applies to MSO expressible optimization problems, such as Minimum Vertex Cover, Minimum Dominating Set, and Maximum Clique. We show that these problems admit a polynomial annotated kernel with a linear number of vertices.

Connected through hyperedge HE-1 (induced by source paper "measuring what matters a hybrid approach to dynamic programming with treewidth"):
  with members:
    - "finding hamiltonian cycle in graphs of bounded treewidth experimental evaluation"
    - "slightly superexponential parameterized problems"
    - "a unified polynomial time algorithm for feedback vertex set on graphs of bounded mim width"
    - "a polynomial kernel for distance hereditary vertex deletion"
    - "combining treewidth and backdoors for csp"
    - "a single exponential fixed parameter algorithm for distance hereditary vertex deletion"
    - "maximum matching width new characterizations and a fast algorithm for dominating set"
    - "meta kernelization using well structured modulators"

Connected through hyperedge HE-2 (induced by source paper "how much does a treedepth modulator help to obtain polynomial kernels beyond sparse graphs"):
  with members:
    - "bidimensionality and kernels"
    - "vertex cover structural parameterization revisited"
    - "meta kernelization using well structured modulators"
    - "a faster parameterized algorithm for treedepth"
    - "explicit linear kernels via dynamic programming"
    - "kernelization lower bounds by cross composition"
    - "linear kernels and single exponential algorithms via protrusion decompositions"
    - "dynamic programming for graphs on surfaces"

Connected through hyperedge HE-3 (induced by source paper "meta kernelization using well structured modulators"):
  with members:
    - "bidimensionality and kernels"
    - "solving problems on graphs of high rank width"
    - "kernelization using structural parameters on sparse graph classes"
    - "kernelization lower bounds by cross composition"
    - "linear kernels and single exponential algorithms via protrusion decompositions"
    - "preprocessing subgraph and minor problems when does a small vertex cover help"
    - "kernel bounds for path and cycle problems"
    - "preprocessing for treewidth a combinatorial analysis through kernelization"

Connected through hyperedge HE-4 (induced by source paper "solving problems on graphs of high rank width"):
  with members:
    - "meta kernelization using well structured modulators"
    - "on feedback vertex set new measure and new structures"
    - "chordal editing is fixed parameter tractable"
    - "kernelization using structural parameters on sparse graph classes"
    - "backdoors to satisfaction"
    - "practical and efficient split decomposition via graph labelled trees"
    - "kernel bounds for path and cycle problems"
    - "linear time split decomposition revisited"

Connected through hyperedge HE-5 (induced by source paper "polynomial kernels collapse the w hierarchy"):
  with members:
    - "bidimensionality and kernels"

Connected through hyperedge HE-6 (induced by source paper "linear kernels and single exponential algorithms via protrusion decompositions"):
  with members:
    - "slightly superexponential parameterized problems"
    - "bidimensionality and kernels"
    - "myhill nerode methods for hypergraphs"
    - "hitting and harvesting pumpkins"
    - "linear recognition of almost interval graphs"
    - "kernelization using structural parameters on sparse graph classes"
    - "interval deletion is fixed parameter tractable"
    - "planar f deletion approximation and optimal fpt algorithms"

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)