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: "public wi fi monetization via advertising"
  Abstract: The proliferation of public Wi-Fi hotspots has brought new business potentials for Wi-Fi networks, which carry a significant amount of global mobile data traffic today. In this paper, we propose a novel Wi-Fi monetization model for venue owners (VOs) deploying public Wi-Fi hotspots, where the VOs can generate revenue by providing two different Wi-Fi access schemes for mobile users (MUs): (i) the premium access, in which MUs directly pay VOs for their Wi-Fi usage, and (ii) the advertising sponsored access, in which MUs watch advertisements in exchange of the free usage of Wi-Fi. VOs sell their ad spaces to advertisers (ADs) via an ad platform, and share the ADs' payments with the ad platform. We formulate the economic interactions among the ad platform, VOs, MUs, and ADs as a three-stage Stackelberg game. In Stage I, the ad platform announces its advertising revenue sharing policy. In Stage II, VOs determine the Wi-Fi prices (for MUs) and advertising prices (for ADs). In Stage III, MUs make access choices and ADs purchase advertising spaces. We analyze the sub-game perfect equilibrium (SPE) of the proposed game systematically, and our analysis shows the following useful observations. First, the ad platform's advertising revenue sharing policy in Stage I will affect only the VOs' Wi-Fi prices but not the VOs' advertising prices in Stage II. Second, both the VOs' Wi-Fi prices and advertising prices are non-decreasing in the advertising concentration level and non-increasing in the MU visiting frequency. Numerical results further show that the VOs are capable of generating large revenues through mainly providing one type of Wi-Fi access (the premium access or advertising sponsored access), depending on their advertising concentration levels and MU visiting frequencies.

Connected through hyperedge HE-1 (induced by source paper "analyzing location based advertising for vehicle service providers using effective resistances"):
  with members:
    - "spatio temporal pricing for ridesharing platforms"
    - "prices and subsidies in the sharing economy"
    - "pricing and optimization in shared vehicle systems an approximation framework"
    - "effective and efficient approximations of the generalized inverse of the graph laplacian matrix with an application to current flow betweenness centrality"

Connected through hyperedge HE-2 (induced by source paper "pricing for collaboration between online apps and offline venues"):
  with members:
    - "the geography of pokemon go beneficial and problematic effects on places and movement"
    - "the cost of free spectrum"
    - "mobile augmented reality survey a bottom up approach"

Connected through hyperedge HE-3 (induced by source paper "achieving an efficient and fair equilibrium through taxation"):
  with members:
    - "two sided matching based cooperative spectrum sharing"
    - "economic analysis of crowdsourced wireless community networks"
    - "efficient and fair collaborative mobile internet access"
    - "an integrated spectrum and information market for green cognitive communications"
    - "mine gold to deliver green cognitive communications"
    - "combining spot and futures markets a hybrid market approach to dynamic spectrum access"
    - "the robust price of anarchy of altruistic games"
    - "stable nash equilibria of medium access games under symmetric socially altruistic behavior"

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)