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: "generalizing the single crossing property on lines and trees to intermediate preferences on median graphs"
  Abstract: Demange (2012) generalized the classical single-crossing property to the intermediate property on median graphs and proved that the representative voter theorem still holds for this more general framework. We complement her result with proving that the linear orders of any profile which is intermediate on a median graph form a Condorcet domain. We prove that for any median graph there exists a profile that is intermediate with respect to that graph and that one may need at least as many alternatives as vertices to construct such a profile. We provide a polynomial-time algorithm to recognize whether or not a given profile is intermediate with respect to some median graph. Finally, we show that finding winners for the Chamberlin-Courant rule is polynomial-time solvable for profiles that are single-crossing on a tree.

Connected through hyperedge HE-1 (induced by source paper "sequential deliberation for social choice"):
  with members:
    - "of the people voting is more effective with representative candidates"
    - "metric distortion of social choice rules lower bounds and fairness properties"
    - "towards large scale deliberative decision making small groups and the importance of triads"
    - "randomized social choice functions under metric preferences"
    - "on voting and facility location"

Connected through hyperedge HE-2 (induced by source paper "towards large scale deliberative decision making small groups and the importance of triads"):
  with members:
    - "crowdsourcing for participatory democracies efficient elicitation of social choice functions"
    - "notes on randomized algorithms"
    - "triadic consensus a randomized algorithm for voting in a crowd"

Connected through hyperedge HE-3 (induced by source paper "are there any nicely structured preference profiles nearby"):
  with members:
    - "computational aspects of nearly single peaked electorates"
    - "the one dimensional euclidean domain finitely many obstructions are not enough"
    - "parameterized algorithmics for computational social choice nine research challenges"
    - "combinatorial voter control in elections"
    - "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"

Connected through hyperedge HE-4 (induced by source paper "finding a collective set of items from proportional multirepresentation to group recommendation"):
  with members:
    - "structure in dichotomous preferences"
    - "properties of multiwinner voting rules"
    - "ptas for minimax approval voting"
    - "computational aspects of multi winner approval voting"
    - "approximating the maxcover problem with bounded frequencies in fpt time"
    - "on the computation of fully proportional representation"
    - "a social welfare optimal sequential allocation procedure"
    - "the complexity of fully proportional representation for single crossing electorates"

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)