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 "large induced subgraphs via triangulations and cmso"):
  Abstract: We obtain an algorithmic meta-theorem for the following optimization problem. Let \phi\ be a Counting Monadic Second Order Logic (CMSO) formula and t be an integer. For a given graph G, the task is to maximize |X| subject to the following: there is a set of vertices F of G, containing X, such that the subgraph G[F] induced by F is of treewidth at most t, and structure (G[F],X) models \phi. #R##N#Some special cases of this optimization problem are the following generic examples. Each of these cases contains various problems as a special subcase: #R##N#1) "Maximum induced subgraph with at most l copies of cycles of length 0 modulo m", where for fixed nonnegative integers m and l, the task is to find a maximum induced subgraph of a given graph with at most l vertex-disjoint cycles of length 0 modulo m. #R##N#2) "Minimum \Gamma-deletion", where for a fixed finite set of graphs \Gamma\ containing a planar graph, the task is to find a maximum induced subgraph of a given graph containing no graph from \Gamma\ as a minor. #R##N#3) "Independent \Pi-packing", where for a fixed finite set of connected graphs \Pi, the task is to find an induced subgraph G[F] of a given graph G with the maximum number of connected components, such that each connected component of G[F] is isomorphic to some graph from \Pi. #R##N#We give an algorithm solving the optimization problem on an n-vertex graph G in time O(#pmc n^{t+4} f(t,\phi)), where #pmc is the number of all potential maximal cliques in G and f is a function depending of t and \phi\ only. We also show how a similar running time can be obtained for the weighted version of the problem. Pipelined with known bounds on the number of potential maximal cliques, we deduce that our optimization problem can be solved in time O(1.7347^n) for arbitrary graphs, and in polynomial time for graph classes with polynomial number of minimal separators.

Includes members:
  Member "exact algorithms for maximum independent set":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "hitting topological minors is fpt")
  Member "bidimensionality and kernels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "hitting topological minors is fpt")
  Member "subexponential parameterized algorithm for minimum fill in":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "subexponential parameterized algorithms and kernelization on almost chordal graphs")
  Member "algorithmic meta theorems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "nowhere dense graph classes and algorithmic applications a tutorial at highlights of logic games and automata 2019")
  Member "finding induced subgraphs via minimal triangulations":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "induced subgraphs of bounded treewidth and the container method")
  Member "treewidth computation and extremal combinatorics":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a heuristic use of dynamic programming to upperbound treewidth")
  Member "deciding first order properties of locally tree decomposable structures":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "hitting topological minors is fpt")

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)