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 "the graph motif problem parameterized by the structure of the input graph"):
  Abstract: The Graph Motif problem was introduced in 2006 in the context of biological networks. It consists of deciding whether or not a multiset of colors occurs in a connected subgraph of a vertex-colored graph. Graph Motif has been mostly analyzed from the standpoint of parameterized complexity. The main parameters which came into consideration were the size of the multiset and the number of colors. In the many utilizations of Graph Motif, however, the input graph originates from real-life applications and has structure. Motivated by this prosaic observation, we systematically study its complexity relatively to graph structural parameters. For a wide range of parameters, we give new or improved FPT algorithms, or show that the problem remains intractable. For the FPT cases, we also give some kernelization lower bounds as well as some ETH-based lower bounds on the worst case running time. Interestingly, we establish that Graph Motif is W[1]-hard (while in W[P]) for parameter max leaf number, which is, to the best of our knowledge, the first problem to behave this way.

Includes members:
  Member "slightly superexponential parameterized problems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the complexity of finding large odd induced subgraphs and odd colorings")
  Member "on problems as hard as cnf sat":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "coarse grained complexity for dynamic algorithms")
  Member "finding and counting vertex colored subtrees":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a survey on subgraph counting concepts algorithms and applications to network motifs and graphlets")
  Member "using neighborhood diversity to solve hard problems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "iterated type partitions")
  Member "kernelization lower bounds by cross composition":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "subexponential parameterized algorithms and kernelization on almost chordal graphs")
  Member "algorithms for jumbled pattern matching in strings":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "generating a gray code for prefix normal words in amortized polylogarithmic time per word")
  Member "constrained multilinear detection for faster functional motif discovery":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "finding temporal patterns using algebraic fingerprints")
  Member "known algorithms for edge clique cover are probably optimal":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "potential maximal cliques parameterized by edge clique cover")

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)