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: "models for truthful online double auctions"
  Abstract: Online double auctions (DAs) model a dynamic two-sided matching problem with private information and self-interest, and are relevant for dynamic resource and task allocation problems. We present a general method to design truthful DAs, such that no agent can benefit from misreporting its arrival time, duration, or value. The family of DAs is parameterized by a pricing rule, and includes a generalization of McAfee's truthful DA to this dynamic setting. We present an empirical study, in which we study the allocative-surplus and agent surplus for a number of different DAs. Our results illustrate that dynamic pricing rules are important to provide good market efficiency for markets with high volatility or low volume.

Connected through hyperedge HE-1 (induced by source paper "bulow klemperer style results for welfare maximization in two sided markets"):
  with members:
    - "the vickrey auction with a single duplicate bidder approximates the optimal revenue"
    - "99 revenue via enhanced competition"
    - "the best of both worlds asymptotically efficient mechanisms with a guarantee on the expected gains from trade"
    - "are two samples really better than one on the non asymptotic performance of empirical revenue maximization"
    - "optimal and benchmark optimal competition complexity for additive buyers over independent items"
    - "approximating gains from trade in two sided markets via simple mechanisms"
    - "submultiplicative glivenko cantelli and uniform convergence of revenues"
    - "a general theory of sample complexity for multi item profit maximization"

Connected through hyperedge HE-2 (induced by source paper "online participatory sensing in double auction environment with location information"):
  with members:
    - "quality adaptive online double auction in participatory sensing"
    - "incentive mechanisms for participatory sensing survey and research challenges"
    - "participatory privacy enabling privacy in participatory sensing"

Connected through hyperedge HE-3 (induced by source paper "quality adaptive online double auction in participatory sensing"):
  with members:
    - "providing long term participation incentive in participatory sensing"
    - "participatory privacy enabling privacy in participatory sensing"

Connected through hyperedge HE-4 (induced by source paper "the secretary returns"):
  with members:
    - "on variants of the matroid secretary problem"
    - "online vertex weighted bipartite matching and single bid budgeted allocations"
    - "matroid secretary problem in the random assignment model"
    - "algorithms for secretary problems on graphs and hypergraphs"

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)