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: "on the likelihood of single peaked preferences"
  Abstract: This paper contains an extensive combinatorial analysis of the single-peaked domain restriction and investigates the likelihood that an election is single-peaked. We provide a very general upper bound result for domain restrictions that can be defined by certain forbidden configurations. This upper bound implies that many domain restrictions (including the single-peaked restriction) are very unlikely to appear in a random election chosen according to the Impartial Culture assumption. For single-peaked elections, this upper bound can be refined and complemented by a lower bound that is asymptotically tight. In addition, we provide exact results for elections with few voters or candidates. Moreover, we consider the Polya urn model and the Mallows model and obtain lower bounds showing that single-peakedness is considerably more likely to appear for certain parameterizations.

Connected through hyperedge HE-1 (induced by source paper "incomplete preferences in single peaked electorates"):
  with members:
    - "computational aspects of nearly single peaked electorates"
    - "recognising multidimensional euclidean preferences"
    - "modeling single peakedness for votes with ties"
    - "single peaked consistency for weak orders is easy"
    - "reinstating combinatorial protections for manipulation and bribery in single peaked and nearly single peaked electorates"
    - "the one dimensional euclidean domain finitely many obstructions are not enough"
    - "complexity of manipulative actions when voting with ties"
    - "are there any nicely structured preference profiles nearby"

Connected through hyperedge HE-2 (induced by source paper "individual based stability in hedonic diversity games"):
  with members:
    - "convergence and hardness of strategic schelling segregation"
    - "schelling games on graphs"
    - "hedonic diversity games"
    - "fractional hedonic games"
    - "generating single peaked votes"
    - "eliciting single peaked preferences using comparison queries"

Connected through hyperedge HE-3 (induced by source paper "computational aspects of nearly single peaked electorates"):
  with members:
    - "are there any nicely structured preference profiles nearby"
    - "structure in dichotomous preferences"
    - "the control complexity of r approval from the single peaked case to the general case"
    - "on the computation of fully proportional representation"
    - "the complexity of fully proportional representation for single crossing electorates"
    - "the complexity of manipulative attacks in nearly single peaked electorates"
    - "clone structures in voters preferences"
    - "the shield that never was societies with single peaked preferences are more open to manipulation and control"

Connected through hyperedge HE-4 (induced by source paper "recognising multidimensional euclidean preferences"):
  with members:
    - "the one dimensional euclidean domain finitely many obstructions are not enough"
    - "on the computation of fully proportional representation"
    - "clone structures in voters preferences"
    - "the shield that never was societies with single peaked preferences are more open to manipulation and control"

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.GT(Computer Science and Game Theory)