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: "on polynomial kernels for structural parameterizations of odd cycle transversal"
  Abstract: The Odd Cycle Transversal problem (OCT) asks whether a given graph can be made bipartite (i.e., 2-colorable) by deleting at most l vertices. We study structural parameterizations of OCT with respect to their polynomial kernelizability, i.e., whether instances can be efficiently reduced to a size polynomial in the chosen parameter. It is a major open problem in parameterized complexity whether Odd Cycle Transversal admits a polynomial kernel when parameterized by l. On the positive side, we show a polynomial kernel for OCT when parameterized by the vertex deletion distance to the class of bipartite graphs of treewidth at most w (for any constant w); this generalizes the parameter feedback vertex set number (i.e., the distance to a forest). Complementing this, we exclude polynomial kernels for OCT parameterized by the distance to outerplanar graphs, conditioned on the assumption that NP \not \subseteq coNP/poly. Thus the bipartiteness requirement for the treewidth w graphs is necessary. Further lower bounds are given for parameterization by distance from cluster and co-cluster graphs respectively, as well as for Weighted OCT parameterized by the vertex cover number (i.e., the distance from an independent set).

Connected through hyperedge HE-1 (induced by source paper "characterizing the easy to find subgraphs from the viewpoint of polynomial time algorithms kernels and turing kernels"):
  with members:
    - "turing kernelization for finding long paths and cycles in restricted graph classes"
    - "a polynomial turing kernel for weighted independent set in bull free graphs"
    - "the parameterized complexity of k biclique"
    - "everything you always wanted to know about the parameterized complexity of subgraph isomorphism but were afraid to ask"
    - "data reduction for graph coloring problems"
    - "kernelization lower bounds by cross composition"
    - "kernelization of packing problems"
    - "kernel bounds for path and cycle problems"

Connected through hyperedge HE-2 (induced by source paper "on structural parameterizations for the 2 club problem"):
  with members:
    - "kernel bounds for structural parameterizations of pathwidth"
    - "the h index of a graph and its application to dynamic subgraph statistics"

Connected through hyperedge HE-3 (induced by source paper "kernelization lower bounds by cross composition"):
  with members:
    - "data reduction for graph coloring problems"
    - "kernelization of packing problems"
    - "representative sets and irrelevant vertices new tools for kernelization"
    - "kernel bounds for path and cycle problems"
    - "clique cover and graph separation new incompressibility results"
    - "preprocessing for treewidth a combinatorial analysis through kernelization"
    - "co nondeterminism in compositions a kernelization lower bound for a ramsey type problem"
    - "compression via matroids a randomized polynomial kernel for odd cycle transversal"

Connected through hyperedge HE-4 (induced by source paper "preprocessing subgraph and minor problems when does a small vertex cover help"):
  with members:
    - "bidimensionality and kernels"
    - "data reduction for graph coloring problems"
    - "kernel bounds for structural parameterizations of pathwidth"
    - "hierarchies of inefficient kernelizability"
    - "kernel bounds for path and cycle problems"
    - "preprocessing for treewidth a combinatorial analysis through kernelization"
    - "compression via matroids a randomized polynomial kernel for odd cycle transversal"
    - "vertex cover kernelization revisited upper and lower bounds for a refined parameter"

Connected through hyperedge HE-5 (induced by source paper "faster parameterized algorithms using linear programming"):
  with members:
    - "representative sets and irrelevant vertices new tools for kernelization"
    - "preprocessing for treewidth a combinatorial analysis through kernelization"
    - "on multiway cut parameterized above lower bounds"
    - "vertex cover kernelization revisited upper and lower bounds for a refined parameter"
    - "almost 2 sat is fixed parameter tractable"

Connected through hyperedge HE-6 (induced by source paper "hierarchies of inefficient kernelizability"):
  with members:
    - "data reduction for graph coloring problems"
    - "kernel bounds for path and cycle problems"
    - "cross composition a new technique for kernelization lower bounds"
    - "solving max r sat above a tight lower bound"
    - "preprocessing of min ones problems a dichotomy"
    - "polynomial time data reduction for dominating set"

Connected through hyperedge HE-7 (induced by source paper "preprocessing for treewidth a combinatorial analysis through kernelization"):
  with members:
    - "data reduction for graph coloring problems"
    - "kernel bounds for structural parameterizations of pathwidth"
    - "kernel bounds for path and cycle problems"
    - "cross composition a new technique for kernelization lower bounds"

Connected through hyperedge HE-8 (induced by source paper "vertex cover kernelization revisited upper and lower bounds for a refined parameter"):
  with members:
    - "preprocessing for treewidth a combinatorial analysis through kernelization"
    - "cross composition a new technique for kernelization lower bounds"
    - "vertex cover problem parameterized above and below tight bounds"
    - "almost 2 sat 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)