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 "approximation and kernelization for chordal vertex deletion"):
  Abstract: The Chordal Vertex Deletion (ChVD) problem asks to delete a minimum number of vertices from an input graph to obtain a chordal graph. In this paper we develop a polynomial kernel for ChVD under the parameterization by the solution size, as well as poly(opt) approximation algorithm. The first result answers an open problem of Marx from 2006 [WG 2006, LNCS 4271, 37-48].

Includes members:
  Member "uniform kernelization complexity of hitting forbidden minors":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a turing kernelization dichotomy for structural parameterizations of mathcal f minor free deletion")
  Member "linear recognition of almost interval graphs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "subexponential parameterized algorithms and kernelization on almost chordal graphs")
  Member "a subexponential parameterized algorithm for proper interval completion":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "lower bounds for the parameterized complexity of minimum fill in and other completion problems")
  Member "kernelization using structural parameters on sparse graph classes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on the parameterized complexity of reconfiguration of connected dominating sets")
  Member "a polynomial kernel for proper interval vertex deletion":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "subexponential parameterized algorithms and kernelization on almost chordal graphs")
  Member "preprocessing subgraph and minor problems when does a small vertex cover help":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "measuring what matters a hybrid approach to dynamic programming with treewidth")
  Member "approximation and tidying a problem kernel for s plex cluster vertex deletion":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "on adaptive algorithms for maximum matching")
  Member "representative sets and irrelevant vertices new tools for kernelization":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "on quasipolynomial multicut mimicking networks and kernelization of multiway cut problems")

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)