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 in mixed graphs"
  Abstract: A mixed graph is a graph with both directed and undirected edges. We present an algorithm for deciding whether a given mixed graph on $n$ vertices contains a feedback vertex set (FVS) of size at most $k$, in time $2^{O(k)}k! O(n^4)$. This is the first fixed parameter tractable algorithm for FVS that applies to both directed and undirected graphs.

Connected through hyperedge HE-1 (induced by source paper "hitting long directed cycles is fixed parameter tractable"):
  with members:
    - "reducing cmso model checking to highly connected graphs"
    - "dag width and circumference of digraphs"
    - "on feedback vertex set new measure and new structures"
    - "a randomized algorithm for long directed cycle"
    - "representative sets of product families"
    - "representative families a unified tradeoff based approach"
    - "the directed grid theorem"
    - "faster deterministic feedback vertex set"

Connected through hyperedge HE-2 (induced by source paper "efficient algorithms for measuring the funnel likeness of dags"):
  with members:
    - "directed subset feedback vertex set is fixed parameter tractable"
    - "kernels for feedback arc set in tournaments"

Connected through hyperedge HE-3 (induced by source paper "directed subset feedback vertex set is fixed parameter tractable"):
  with members:
    - "clustering with local restrictions"
    - "on feedback vertex set new measure and new structures"
    - "faster parameterized algorithms using linear programming"
    - "fixed parameter tractability of multicut in directed acyclic graphs"
    - "representative sets and irrelevant vertices new tools for kernelization"
    - "clique cover and graph separation new incompressibility results"
    - "solving connectivity problems parameterized by treewidth in single exponential time"
    - "compression via matroids a randomized polynomial kernel for odd cycle transversal"

Connected through hyperedge HE-4 (induced by source paper "backdoors to tractable answer set programming"):
  with members:
    - "guarantees and limits of preprocessing in constraint satisfaction and reasoning"
    - "the parameterized complexity of reasoning problems beyond np"
    - "backdoors to normality for disjunctive logic programs"
    - "numvc an efficient local search algorithm for minimum vertex cover"
    - "backdoors to abduction"
    - "the good the bad and the odd cycles in answer set programs"
    - "strong backdoors to bounded treewidth sat"
    - "strong backdoors to nested satisfiability"

Connected through hyperedge HE-5 (induced by source paper "backdoors to satisfaction"):
  with members:
    - "the good the bad and the odd cycles in answer set programs"
    - "strong backdoors to bounded treewidth sat"
    - "strong backdoors to nested satisfiability"
    - "augmenting tractable fragments of abstract argumentation"
    - "backdoors to acyclic sat"
    - "3 sat faster and simpler unique sat bounds for ppsz hold in general"
    - "backdoors to tractable answer set programming"
    - "limits of preprocessing"

Connected through hyperedge HE-6 (induced by source paper "a universally fastest algorithm for max 2 sat max 2 csp and everything in between"):
  with members:
    - "a new upper bound for max 2 sat a graph theoretic approach"
    - "3 coloring in time o 1 3289 n"

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)