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: "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.

Connected through hyperedge HE-1 (induced by source paper "tight bounds for planar strongly connected steiner subgraph with fixed number of terminals and extensions"):
  with members:
    - "fpt inapproximability of directed cut and connectivity problems"
    - "complexity of the steiner network problem with respect to the number of terminals"
    - "the parameterized complexity of finding point sets with hereditary properties"
    - "homomorphisms are a good basis for counting small subgraphs"
    - "parameterized approximation algorithms for directed steiner network problems"
    - "on subexponential parameterized algorithms for steiner tree and directed subset tsp on planar graphs"
    - "on the parameterized complexity of red blue points separation"
    - "subexponential parameterized algorithms for planar and apex minor free graphs via low treewidth pattern covering"

Connected through hyperedge HE-2 (induced by source paper "balanced connected subgraph problem in geometric intersection graphs"):
  with members:
    - "the balanced connected subgraph problem"

Connected through hyperedge HE-3 (induced by source paper "graph motif problems parameterized by dual"):
  with members:
    - "kernelization lower bounds by cross composition"

Connected through hyperedge HE-4 (induced by source paper "the balanced connected subgraph problem"):
  with members:
    - "balanced partitions of 3 colored geometric sets in the plane"
    - "solving the maximum weight connected subgraph problem to optimality"
    - "maximum balanced subgraph problem parameterized above lower bound"

Connected through hyperedge HE-5 (induced by source paper "simplified algorithmic metatheorems beyond mso treewidth and neighborhood diversity"):
  with members:
    - "parameterized complexity of fair deletion problems"
    - "on the parameterized complexity of recognizing well covered r l graphs"
    - "algorithms and hardness results for happy coloring problems"
    - "anti path cover on sparse graph classes"
    - "target set selection in dense graph classes"
    - "extension complexity mso logic and treewidth"
    - "on the parameterized complexity of computing balanced partitions in graphs"
    - "fixed parameter complexity of distance constrained labeling and uniform channel assignment problems"

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)