human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "kernels for connected dominating set on graphs with excluded topological subgraphs"):
  Abstract: We give the first linear kernels for the (Connected) Dominating Set problems on H-topological minor free graphs. We prove the existence of polynomial time algorithms that, for a given H-topological-minor-free graph G and a positive integer k, output an H-topological-minor-free graph G' on O(k) vertices such that G has a (connected) dominating set of size k iff G' has one. Our results extend the known classes of graphs on which the Dominating Set and Connected Dominating Set problems admit linear kernels. Prior to our work, it was known that these problems admit linear kernels on graphs excluding a fixed apex graph H as a minor. Moreover, for Dominating Set, a kernel of size kc(H), where c(H) is a constant depending on the size of H, follows from a more general result on the kernelization of Dominating Set on graphs of bounded degeneracy. Alon and Gutner explicitly asked whether one can obtain a linear kernel for Dominating Set on H-minor-free graphs. We answer this question in the affirmative and in fact prove a more general result. For Connected Dominating Set no polynomial kernel even on H-minor-free graphs was known prior to our work. On the negative side, it is known that Connected Dominating Set on 2-degenerated graphs does not admit a polynomial kernel unless coNP $\subseteq$ NP/poly. Our kernelization algorithm is based on a non-trivial combination of the following ingredients The structural theorem of Grohe and Marx [STOC 2012] for graphs excluding a fixed graph H as a topological minor; A novel notion of protrusions, different than the one defined in [FOCS 2009]; Our results are based on a generic reduction rule that produces an equivalent instance (in case the input graph is H-minor-free) of the problem, with treewidth $O(\sqrt{k})$. The application of this rule in a divide-and-conquer fashion, together with the new notion of protrusions, gives us the linear kernels.

Includes members:
  Member "tight kernel bounds for problems on graphs with small degeneracy":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "lossy kernels for connected dominating set on sparse graphs")
  Member "linear kernels and single exponential algorithms via protrusion decompositions":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "hitting topological minors is fpt")
  Member "parameterized complexity of directed steiner tree on sparse graphs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "tight bounds for planar strongly connected steiner subgraph with fixed number of terminals and extensions")
  Member "structure theorem and isomorphism test for graphs with excluded topological subgraphs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "hypergraph isomorphism for groups with restricted composition factors")
  Member "bidimensionality and geometric graphs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "planar graphs have bounded queue number")
  Member "hitting forbidden minors approximation and kernelization":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "structural parameterization for graph deletion problems over data streams")
  Member "bidimensionality and eptas":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "improved in approximability bounds for d scattered set")
  Member "beyond bidimensionality parameterized subexponential algorithms on directed graphs":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "detecting and counting small patterns in planar graphs in subexponential parameterized time")

Question: Please tell me which class the source paper 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)