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: "kernelization and sparseness the case of dominating set"
  Abstract: We prove that for every positive integer $r$ and for every graph class $\mathcal G$ of bounded expansion, the $r$-Dominating Set problem admits a linear kernel on graphs from $\mathcal G$. Moreover, when $\mathcal G$ is only assumed to be nowhere dense, then we give an almost linear kernel on $\mathcal G$ for the classic Dominating Set problem, i.e., for the case $r=1$. These results generalize a line of previous research on finding linear kernels for Dominating Set and $r$-Dominating Set. However, the approach taken in this work, which is based on the theory of sparse graphs, is radically different and conceptually much simpler than the previous approaches. #R##N#We complement our findings by showing that for the closely related Connected Dominating Set problem, the existence of such kernelization algorithms is unlikely, even though the problem is known to admit a linear kernel on $H$-topological-minor-free graphs. Also, we prove that for any somewhere dense class $\mathcal G$, there is some $r$ for which $r$-Dominating Set is W[$2$]-hard on $\mathcal G$. Thus, our results fall short of proving a sharp dichotomy for the parameterized complexity of $r$-Dominating Set on subgraph-monotone graph classes: we conjecture that the border of tractability lies exactly between nowhere dense and somewhere dense graph classes.

Connected through hyperedge HE-1 (induced by source paper "domination above r independence does sparseness help"):
  with members:
    - "neighborhood complexity and kernelization for nowhere dense classes of graphs"
    - "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"
    - "polynomial time data reduction for dominating set"

Connected through hyperedge HE-2 (induced by source paper "parameterized circuit complexity of model checking first order logic on sparse structures"):
  with members:
    - "distributed domination on graph classes of bounded expansion"
    - "polynomial kernels and wideness properties of nowhere dense graph classes"
    - "neighborhood complexity and kernelization for nowhere dense classes of graphs"

Connected through hyperedge HE-3 (induced by source paper "progressive algorithms for domination and independence"):
  with members:
    - "on the number of types in sparse graphs"
    - "neighborhood complexity and kernelization for nowhere dense classes of graphs"

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 "algorithmic properties of sparse digraphs"):
  with members:
    - "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"
    - "kernelization using structural parameters on sparse graph classes"
    - "parameterized complexity of directed steiner tree on sparse graphs"

Connected through hyperedge HE-6 (induced by source paper "on the number of types in sparse graphs"):
  with members:
    - "characterising bounded expansion by neighbourhood complexity"
    - "polynomial kernels and wideness properties of nowhere dense graph classes"
    - "neighborhood complexity and kernelization for nowhere dense classes of graphs"
    - "deciding first order properties of nowhere dense graphs"
    - "homomorphism preservation on quasi wide classes"

Connected through hyperedge HE-7 (induced by source paper "being even slightly shallow makes life hard"):
  with members:
    - "kernelization using structural parameters on sparse graph classes"
    - "solving connectivity problems parameterized by treewidth in single exponential time"
    - "problems parameterized by treewidth tractable in single exponential time a logical approach"
    - "minimum weight triangulation is np hard"

Connected through hyperedge HE-8 (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 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"
    - "homomorphism preservation on quasi wide classes"

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)