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: "ranking and tradeoffs in sponsored search auctions"
  Abstract: In a sponsored search auction, decisions about how to rank ads impose tradeoffs between objectives such as revenue and welfare. In this paper, we examine how these tradeoffs should be made. We begin by arguing that the most natural solution concept to evaluate these tradeoffs is the lowest symmetric Nash equilibrium (SNE). As part of this argument, we generalise the well known connection between the lowest SNE and the VCG outcome. We then propose a new ranking algorithm, loosely based on the revenue-optimal auction, that uses a reserve price to order the ads (not just to filter them) and give conditions under which it raises more revenue than simply applying that reserve price. Finally, we conduct extensive simulations examining the tradeoffs enabled by different ranking algorithms and show that our proposed algorithm enables superior operating points by a variety of metrics.

Connected through hyperedge HE-1 (induced by source paper "a price per attention auction scheme using mouse cursor information"):
  with members:
    - "attention is all you need"
    - "optimising trade offs among stakeholders in ad auctions"
    - "doubleclick ad exchange auction"

Connected through hyperedge HE-2 (induced by source paper "optimizing trade offs among stakeholders in real time bidding by incorporating multimedia metrics"):
  with members:
    - "risk aware dynamic reserve prices of programmatic guarantee in display advertising"
    - "a dynamic pricing model for unifying programmatic guarantee and real time bidding in display advertising"
    - "optimising trade offs among stakeholders in ad auctions"
    - "a lattice framework for pricing display advertisement options with the stochastic volatility underlying model"
    - "multi keyword multi click advertisement option contracts for sponsored search"

Connected through hyperedge HE-3 (induced by source paper "the sample complexity of auctions with side information"):
  with members:
    - "the sample complexity of revenue maximization"
    - "sampling and representation complexity of revenue maximization"
    - "making the most of your samples"
    - "vickrey auctions for irregular distributions"

Connected through hyperedge HE-4 (induced by source paper "computational analysis of perfect information position auctions"):
  with members:
    - "graphical models for game theory"
    - "computing nash equilibria of action graph games"
    - "constrained automated mechanism design for infinite games of incomplete information"
    - "sponsored search auctions with markovian users"

Connected through hyperedge HE-5 (induced by source paper "optimising trade offs among stakeholders in ad auctions"):
  with members:
    - "refine predictions ad infinitum"
    - "efficiency revenue trade offs in auctions"

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)