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: "preprocessing subgraph and minor problems when does a small vertex cover help"
  Abstract: We prove a number of results around kernelization of problems parameterized by the size of a given vertex cover of the input graph. We provide three sets of simple general conditions characterizing problems admitting kernels of polynomial size. Our characterizations not only give generic explanations for the existence of many known polynomial kernels for problems like q-Coloring, Odd Cycle Transversal, Chordal Deletion, Eta Transversal, or Long Path, parameterized by the size of a vertex cover, but also imply new polynomial kernels for problems like F-Minor-Free Deletion, which is to delete at most k vertices to obtain a graph with no minor from a fixed finite set F. #R##N#While our characterization captures many interesting problems, the kernelization complexity landscape of parameterizations by vertex cover is much more involved. We demonstrate this by several results about induced subgraph and minor containment testing, which we find surprising. While it was known that testing for an induced complete subgraph has no polynomial kernel unless NP is in coNP/poly, we show that the problem of testing if a graph contains a complete graph on t vertices as a minor admits a polynomial kernel. On the other hand, it was known that testing for a path on t vertices as a minor admits a polynomial kernel, but we show that testing for containment of an induced path on t vertices is unlikely to admit a polynomial kernel.

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 "structural parameterization for graph deletion problems over data streams"):
  with members:
    - "on the streaming complexity of fundamental geometric problems"
    - "tight bounds for single pass streaming complexity of the set cover problem"
    - "faster deterministic feedback vertex set"
    - "interval deletion is fixed parameter tractable"
    - "linear kernels and single exponential algorithms via protrusion decompositions"
    - "hitting forbidden minors approximation and kernelization"

Connected through hyperedge HE-3 (induced by source paper "fixed parameter tractability of graph deletion problems over data streams"):
  with members:
    - "on the streaming complexity of fundamental geometric problems"
    - "tight bounds for single pass streaming complexity of the set cover problem"

Connected through hyperedge HE-4 (induced by source paper "approximation and kernelization for chordal vertex deletion"):
  with members:
    - "uniform kernelization complexity of hitting forbidden minors"
    - "linear recognition of almost interval graphs"
    - "a subexponential parameterized algorithm for proper interval completion"
    - "kernelization using structural parameters on sparse graph classes"
    - "a polynomial kernel for proper interval vertex deletion"
    - "approximation and tidying a problem kernel for s plex cluster vertex deletion"
    - "representative sets and irrelevant vertices new tools for kernelization"
    - "compression via matroids a randomized polynomial kernel for odd cycle transversal"

Connected through hyperedge HE-5 (induced by source paper "uniform kernelization complexity of hitting forbidden minors"):
  with members:
    - "turing kernelization for finding long paths and cycles in restricted graph classes"
    - "bidimensionality and kernels"
    - "a faster parameterized algorithm for treedepth"
    - "polynomial bounds for the grid minor theorem"
    - "kernelization using structural parameters on sparse graph classes"
    - "network sparsification for steiner problems on planar and bounded genus graphs"
    - "kernel bounds for structural parameterizations of pathwidth"
    - "linear kernels and single exponential algorithms via protrusion decompositions"

Connected through hyperedge HE-6 (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"
    - "meta kernelization with structural parameters"
    - "kernelization lower bounds by cross composition"
    - "linear kernels and single exponential algorithms via protrusion decompositions"
    - "kernel bounds for path and cycle problems"
    - "preprocessing for treewidth a combinatorial analysis through kernelization"

Connected through hyperedge HE-7 (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"
    - "meta kernelization with structural parameters"
    - "interval deletion is fixed parameter tractable"

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)