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: "incorporating hidden costs of annoying ads in display auctions"
  Abstract: Media publisher platforms often face an effectiveness-nuisance tradeoff: more annoying ads can be more effective for some advertisers because of their ability to attract attention, but after attracting viewers' attention, their nuisance to viewers can decrease engagement with the platform over time. With the rise of mobile technology and ad blockers, many platforms are becoming increasingly concerned about how to improve monetization through digital ads while improving viewer experience. #R##N#We study an online ad auction mechanism that incorporates a charge for ad impact on user experience as a criterion for ad selection and pricing. Like a Pigovian tax, the charge causes advertisers to internalize the hidden cost of foregone future platform revenue due to ad impact on user experience. Over time, the mechanism provides an incentive for advertisers to develop ads that are effective while offering viewers a more pleasant experience. We show that adopting the mechanism can simultaneously benefit the publisher, advertisers, and viewers, even in the short term. #R##N#Incorporating a charge for ad impact can increase expected advertiser profits if enough advertisers compete. A stronger effectiveness-nuisance tradeoff, meaning that ad effectiveness is more strongly associated with negative impact on user experience, increases the amount of competition required for the mechanism to benefit advertisers. The findings suggest that the mechanism can benefit the marketplace for ad slots that consistently attract many advertisers.

Connected through hyperedge HE-1 (induced by source paper "heavy tails make happy buyers"):
  with members:
    - "the sample complexity of revenue maximization"
    - "learning valuation distributions from partial observation"

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)