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: "between treewidth and clique width"
  Abstract: Many hard graph problems can be solved efficiently when restricted to graphs of bounded treewidth, and more generally to graphs of bounded clique-width. But there is a price to be paid for this generality, exemplified by the four problems MaxCut, Graph Coloring, Hamiltonian Cycle and Edge Dominating Set that are all FPT parameterized by treewidth but none of which can be FPT parameterized by clique-width unless FPT = W[1], as shown by Fomin et al [7, 8]. We therefore seek a structural graph parameter that shares some of the generality of clique-width without paying this price. Based on splits, branch decompositions and the work of Vatshelle [18] on Maximum Matching-width, we consider the graph parameter sm-width which lies between treewidth and clique-width. Some graph classes of unbounded treewidth, like distance-hereditary graphs, have bounded sm-width. We show that MaxCut, Graph Coloring, Hamiltonian Cycle and Edge Dominating Set are all FPT parameterized by sm-width.

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 "parameterized coloring problems on threshold graphs"):
  with members:
    - "data reduction for graph coloring problems"
    - "algorithms and almost tight results for 3 colorability of small diameter graphs"
    - "cross composition a new technique for kernelization lower bounds"

Connected through hyperedge HE-3 (induced by source paper "computing the chromatic number using graph decompositions via matrix rank"):
  with members:
    - "fine grained parameterized complexity analysis of graph coloring problems"
    - "competitive algorithms for generalized k server in uniform metrics"
    - "cutwidth obstructions and algorithmic aspects"
    - "coloring graphs having few colorings over path decompositions"
    - "parameterized algorithms for modular width"
    - "speeding up dynamic programming with representative sets an experimental evaluation of algorithms for steiner tree on tree decompositions"
    - "data reduction for graph coloring problems"
    - "fast hamiltonicity checking via bases of perfect matchings"

Connected through hyperedge HE-4 (induced by source paper "parameterized compilation lower bounds for restricted cnf formulas"):
  with members:
    - "complexity and approximability of parameterized max csps"
    - "understanding model counting for beta acyclic cnf formulas"
    - "no small nondeterministic read once branching programs for cnfs of bounded treewidth"
    - "on obdds for cnfs of bounded treewidth"
    - "satisfiability of acyclic and almost acyclic cnf formulas"
    - "a knowledge compilation map"

Connected through hyperedge HE-5 (induced by source paper "maximum matching width new characterizations and a fast algorithm for dominating set"):
  with members:
    - "powers of tensors and fast matrix multiplication"
    - "known algorithms on graphs of bounded treewidth are probably optimal"

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)