human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "incentive compatible classification"):
  Abstract: We investigate the possibility of an incentive-compatible (IC, a.k.a. strategy-proof) mechanism for the classification of agents in a network according to their reviews of each other. In the $ \alpha $-classification problem we are interested in selecting the top $ \alpha $ fraction of users. We give upper bounds (impossibilities) and lower bounds (mechanisms) on the worst-case coincidence between the classification of an IC mechanism and the ideal $ \alpha $-classification. We prove bounds which depend on $ \alpha $ and on the maximal number of reviews given by a single agent, $ \Delta $. Our results show that it is harder to find a good mechanism when $ \alpha $ is smaller and $ \Delta $ is larger. In particular, if $ \Delta $ is unbounded, then the best mechanism is trivial (that is, it does not take into account the reviews). On the other hand, when $ \Delta $ is sublinear in the number of agents, we give a simple, natural mechanism, with a coincidence ratio of $ \alpha $.

Includes members:
  Member "a near optimal mechanism for impartial selection":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "impartial selection with additive approximation guarantees")
  Member "optimal impartial selection":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "impartial selection with additive approximation guarantees")
  Member "sum of us strategyproof selection from the selectors":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "impartial selection with additive approximation guarantees")

Question: Please tell me which class the source paper 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)