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: "feedback vertex set inspired kernel for chordal vertex deletion"
  Abstract: Given a graph $G$ and a parameter $k$, the Chordal Vertex Deletion (CVD) problem asks whether there exists a subset $U\subseteq V(G)$ of size at most $k$ that hits all induced cycles of size at least 4. The existence of a polynomial kernel for CVD was a well-known open problem in the field of Parameterized Complexity. Recently, Jansen and Pilipczuk resolved this question affirmatively by designing a polynomial kernel for CVD of size $O(k^{161}\log^{58}k)$, and asked whether one can design a kernel of size $O(k^{10})$. While we do not completely resolve this question, we design a significantly smaller kernel of size $O(k^{12}\log^{10}k)$, inspired by the $O(k^2)$-size kernel for Feedback Vertex Set. Furthermore, we introduce the notion of the independence degree of a vertex, which is our main conceptual contribution.

Connected through hyperedge HE-1 (induced by source paper "subexponential parameterized algorithms and kernelization on almost chordal graphs"):
  with members:
    - "a complexity dichotomy for hitting connected minors on bounded treewidth graphs the chair and the banner draw the boundary"
    - "approximation and kernelization for chordal vertex deletion"
    - "polynomial kernels for weighted problems"
    - "linear recognition of almost interval graphs"
    - "large induced subgraphs via triangulations and cmso"
    - "data reduction for graph coloring problems"
    - "interval deletion is fixed parameter tractable"
    - "kernelization lower bounds by cross composition"

Connected through hyperedge HE-2 (induced by source paper "a polynomial kernel for 3 leaf power deletion"):
  with members:
    - "approximation and kernelization for chordal vertex deletion"
    - "a single exponential fixed parameter algorithm for distance hereditary vertex deletion"
    - "a polynomial kernel for block graph deletion"
    - "chordal editing is fixed parameter tractable"
    - "vertex cover kernelization revisited upper and lower bounds for a refined parameter"
    - "polynomial kernels for 3 leaf power graph modification problems"

Connected through hyperedge HE-3 (induced by source paper "polylogarithmic approximation algorithms for weighted mathcal f deletion problems"):
  with members:
    - "approximation and kernelization for chordal vertex deletion"
    - "bidimensionality and kernels"
    - "lp based robust algorithms for noisy minor free and bounded treewidth graphs"
    - "bidimensionality and geometric graphs"
    - "hitting forbidden minors approximation and kernelization"
    - "bidimensionality and eptas"
    - "hitting diamonds and growing cacti"

Connected through hyperedge HE-4 (induced by source paper "a polynomial kernel for distance hereditary vertex deletion"):
  with members:
    - "approximation and kernelization for chordal vertex deletion"
    - "a single exponential fixed parameter algorithm for distance hereditary vertex deletion"
    - "an fpt algorithm and a polynomial kernel for linear rankwidth 1 vertex deletion"
    - "uniform kernelization complexity of hitting forbidden minors"
    - "linear kernels and single exponential algorithms via protrusion decompositions"
    - "split decomposition and graph labelled trees characterizations and fully dynamic algorithms for totally decomposable graphs"

Connected through hyperedge HE-5 (induced by source paper "a polynomial kernel for block graph deletion"):
  with members:
    - "parameterized vertex deletion problems for hereditary graph classes with a block property"
    - "approximation and kernelization for chordal vertex deletion"
    - "a faster fpt algorithm and a smaller kernel for block graph vertex deletion"
    - "a polynomial kernel for block graph vertex deletion"
    - "on feedback vertex set new measure and new structures"
    - "chordal editing is fixed parameter tractable"
    - "faster deterministic feedback vertex set"
    - "linear kernels and single exponential algorithms via protrusion decompositions"

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)