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 "on the approximate compressibility of connected vertex cover"):
  Abstract: The Connected Vertex Cover problem, where the goal is to compute a minimum set of vertices in a given graph which forms a vertex cover and induces a connected subgraph, is a fundamental combinatorial problem and has received extensive attention in various subdomains of algorithmics. In the area of kernelization, it is known that this problem is unlikely to have efficient preprocessing algorithms, also known as polynomial kernelizations. However, it has been shown in a recent work of Lokshtanov et al. [STOC 2017] that if one considered an appropriate notion of approximate kernelization, then this problem parameterized by the solution size does admit an approximate polynomial kernelization. In fact, Lokhtanov et al. were able to obtain a polynomial size approximate kernelization scheme (PSAKS) for Connected Vertex Cover parameterized by the solution size. A PSAKS is essentially a preprocessing algorithm whose error can be made arbitrarily close to 0. In this paper we revisit this problem, and consider parameters that are strictly smaller than the size of the solution and obtain the first polynomial size approximate kernelization schemes for the Connected Vertex Cover problem when parameterized by the deletion distance of the input graph to the class of cographs, the class of bounded treewidth graphs, and the class of all chordal graphs.

Includes members:
  Member "revisiting connected vertex cover fpt algorithms and lossy kernels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on approximate data reduction for the rural postman problem theory and experiments")
  Member "smaller parameters for vertex cover kernelization":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "elimination distances blocking sets and kernels for vertex cover")
  Member "approximation and kernelization for chordal vertex deletion":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "subexponential parameterized algorithms and kernelization on almost chordal graphs")
  Member "how much does a treedepth modulator help to obtain polynomial kernels beyond sparse graphs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "optimal data reduction for graph coloring using low degree polynomials")
  Member "a randomized polynomial kernelization for vertex cover with a smaller parameter":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "elimination distances blocking sets and kernels for vertex cover")
  Member "vertex cover structural parameterization revisited":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "elimination distances blocking sets and kernels for vertex cover")
  Member "kernelization lower bounds by cross composition":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "subexponential parameterized algorithms and kernelization on almost chordal graphs")
  Member "kernelization of packing problems":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "on kernelization for edge dominating set under structural parameters")

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)