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: "target set selection in dense graph classes"
  Abstract: In this paper we study the Target Set Selection problem, a fundamental problem in computational social choice, from a parameterized complexity perspective. Here for a given graph and a threshold for each vertex the task is to find a set of active vertices that activates whole graph. A vertex becomes active if the number of activated vertices in its neighborhood is at least its threshold. #R##N#We give two parameterized algorithms for a special case where each vertex has threshold set to half of its neighbors (the so called Majority Target Set Selection problem) for parameterizations by neighborhood diversity and twin cover number of the input graph. From the opposite side we give hardness proof for the Majority Target Set Selection problem when parameterized by (restriction of) the modular-width - a natural generalization of both previous structural parameters. Finally, we give hardness proof for the Target Set Selection problem parameterized by the neighborhood diversity when there is no restriction on the thresholds.

Connected through hyperedge HE-1 (induced by source paper "iterated type partitions"):
  with members:
    - "parameterized complexity of equitable coloring"
    - "fully polynomial fpt algorithms for some classes of bounded clique width graphs"
    - "evangelism in social networks algorithms and complexity"
    - "partitioning graphs into induced subgraphs"
    - "parameterized algorithms for modular width"
    - "using neighborhood diversity to solve hard problems"

Connected through hyperedge HE-2 (induced by source paper "solving target set selection with bounded thresholds faster than 2 n"):
  with members:
    - "target set selection parameterized by clique width and maximum threshold"
    - "finding a maximum induced degenerate subgraph faster than 2 n"

Connected through hyperedge HE-3 (induced by source paper "an inapproximability result for the target set selection problem on bipartite graphs"):
  with members:
    - "target set selection problem for honeycomb networks"

Connected through hyperedge HE-4 (induced by source paper "simplified algorithmic metatheorems beyond mso treewidth and neighborhood diversity"):
  with members:
    - "parameterized complexity of fair deletion problems"
    - "the graph motif problem parameterized by the structure of the input graph"
    - "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"
    - "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"

Connected through hyperedge HE-5 (induced by source paper "target set selection parameterized by clique width and maximum threshold"):
  with members:
    - "latency bounded target set selection in social networks"
    - "parameterized inapproximability of target set selection and generalizations"
    - "parameterized algorithms for modular width"
    - "confronting intractability via parameters"

Connected through hyperedge HE-6 (induced by source paper "evangelism in social networks algorithms and complexity"):
  with members:
    - "on finding small sets that influence large networks"
    - "spread of influence in weighted networks under time and budget constraints"
    - "contagious sets in dense graphs"
    - "distance constrained labeling on graphs with bounded neighborhood diversity"
    - "parameterized approximability of maximizing the spread of influence in networks"
    - "latency bounded target set selection in social networks"
    - "using neighborhood diversity to solve hard problems"
    - "algorithmic meta theorems"

Connected through hyperedge HE-7 (induced by source paper "partitioning graphs into induced subgraphs"):
  with members:
    - "star partitions of perfect graphs"
    - "partitioning perfect graphs into stars"
    - "parameterized algorithms for modular width"

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)