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: "preprocessing for treewidth a combinatorial analysis through kernelization"
  Abstract: The notion of treewidth plays an important role in theoretical and practical studies of graph problems. It has been recognized that, especially in practical environments, when computing the treewidth of a graph it is invaluable to first apply an array of preprocessing rules that simplify and shrink it. This work seeks to prove rigorous performance guarantees for such preprocessing rules, both known and new ones, by studying them in the framework of kernelization from parameterized complexity. #R##N#It is known that the NP-complete problem of determining whether a given graph G has treewidth at most k admits no polynomial-time preprocessing algorithm that reduces any input instance to size polynomial in k, unless NP is in coNP/poly and the polynomial hierarchy collapses to its third level. In this paper we therefore consider structural graph measures larger than treewidth, and determine whether efficient preprocessing can shrink the instance size to a polynomial in such a parameter value. #R##N#We prove that given an instance (G,k) of treewidth we can efficiently reduce its size to O(fvs(G)^4) vertices, where fvs(G) is the size of a minimum feedback vertex set in G. We can also prove a size reduction to O(vc(G)^3) vertices, where vc(G) is the size of a minimum vertex cover. Phrased in the language of parameterized complexity, we show that Treewidth has a polynomial kernel when parameterized by the size of a given feedback vertex set, and also by the size of a vertex cover. In contrast we show that Treewidth parameterized by the vertex-deletion distance to a single clique, and Weighted Treewidth parameterized by the size of a vertex cover, do not admit polynomial kernelizations unless NP is in coNP/poly.

Connected through hyperedge HE-1 (induced by source paper "measuring what matters a hybrid approach to dynamic programming with treewidth"):
  with members:
    - "finding hamiltonian cycle in graphs of bounded treewidth experimental evaluation"
    - "slightly superexponential parameterized problems"
    - "a unified polynomial time algorithm for feedback vertex set on graphs of bounded mim width"
    - "a polynomial kernel for distance hereditary vertex deletion"
    - "combining treewidth and backdoors for csp"
    - "a single exponential fixed parameter algorithm for distance hereditary vertex deletion"
    - "maximum matching width new characterizations and a fast algorithm for dominating set"
    - "meta kernelization using well structured modulators"

Connected through hyperedge HE-2 (induced by source paper "feedback vertex set inspired kernel for chordal vertex deletion"):
  with members:
    - "polylogarithmic approximation algorithms for weighted mathcal f deletion problems"
    - "turing kernelization for finding long paths and cycles in restricted graph classes"
    - "approximation and kernelization for chordal vertex deletion"
    - "bidimensionality and kernels"
    - "unit interval vertex deletion fewer vertices are relevant"
    - "uniform kernelization complexity of hitting forbidden minors"
    - "linear recognition of almost interval graphs"
    - "chordal editing is fixed parameter tractable"

Connected through hyperedge HE-3 (induced by source paper "the power of data reduction for matching"):
  with members:
    - "fully polynomial time parameterized computations for graphs and matrices of low treewidth"
    - "polynomial fixed parameter algorithms a case study for longest path on interval graphs"
    - "linear time lexdfs on cocomparability graphs"
    - "navigating central path with electrical flows from flows to matchings and back"
    - "a simple polynomial algorithm for the longest path problem on cocomparability graphs"

Connected through hyperedge HE-4 (induced by source paper "uniform kernelization complexity of hitting forbidden minors"):
  with members:
    - "turing kernelization for finding long paths and cycles in restricted graph classes"
    - "bidimensionality and kernels"
    - "a faster parameterized algorithm for treedepth"
    - "polynomial bounds for the grid minor theorem"
    - "kernelization using structural parameters on sparse graph classes"
    - "network sparsification for steiner problems on planar and bounded genus graphs"
    - "kernel bounds for structural parameterizations of pathwidth"
    - "linear kernels and single exponential algorithms via protrusion decompositions"

Connected through hyperedge HE-5 (induced by source paper "meta kernelization using well structured modulators"):
  with members:
    - "bidimensionality and kernels"
    - "solving problems on graphs of high rank width"
    - "kernelization using structural parameters on sparse graph classes"
    - "meta kernelization with structural parameters"
    - "kernelization lower bounds by cross composition"
    - "linear kernels and single exponential algorithms via protrusion decompositions"
    - "preprocessing subgraph and minor problems when does a small vertex cover help"
    - "kernel bounds for path and cycle problems"

Connected through hyperedge HE-6 (induced by source paper "on sparsification for computing treewidth"):
  with members:
    - "tight kernel bounds for problems on graphs with small degeneracy"
    - "fpt is characterized by useful obstruction sets"
    - "kernelization lower bounds by cross composition"
    - "kernel bounds for structural parameterizations of pathwidth"
    - "kernelization of packing problems"
    - "hitting forbidden minors approximation and kernelization"
    - "cross composition a new technique for kernelization lower bounds"

Connected through hyperedge HE-7 (induced by source paper "meta kernelization with structural parameters"):
  with members:
    - "meta kernelization using well structured modulators"
    - "guarantees and limits of preprocessing in constraint satisfaction and reasoning"
    - "kernelization using structural parameters on sparse graph classes"
    - "linear time split decomposition revisited"

Connected through hyperedge HE-8 (induced by source paper "treewidth and pathwidth parameterized by vertex cover"):
  with members:
    - "kernel bounds for structural parameterizations of pathwidth"

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)