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: "testing top monotonicity"
  Abstract: Top monotonicity is a relaxation of various well-known domain restrictions such as single-peaked and single-crossing for which negative impossibility results are circumvented and for which the median-voter theorem still holds. We examine the problem of testing top monotonicity and present a characterization of top monotonicity with respect to non-betweenness constraints. We then extend the definition of top monotonicity to partial orders and show that testing top monotonicity of partial orders is NP-complete.

Connected through hyperedge HE-1 (induced by source paper "incomplete preferences in single peaked electorates"):
  with members:
    - "on the likelihood of single peaked preferences"
    - "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"

Connected through hyperedge HE-2 (induced by source paper "single peaked consistency for weak orders is easy"):
  with members:
    - "computational aspects of nearly single peaked electorates"
    - "the computational impact of partial votes on strategic voting"
    - "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"
    - "exact analysis of dodgson elections lewis carroll s 1876 voting system is complete for parallel access to np"

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)