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 "pricing average price advertising options when underlying spot market prices are discontinuous"):
  Abstract: Advertising options have been recently studied as a special type of guaranteed contracts in online advertising, which are an alternative sales mechanism to real-time auctions. An advertising option is a contract which gives its buyer a right but not obligation to enter into transactions to purchase page views or link clicks at one or multiple pre-specified prices in a specific future period. Different from typical guaranteed contracts, the option buyer pays a lower upfront fee but can have greater flexibility and more control of advertising. Many studies on advertising options so far have been restricted to the situations where the option payoff is determined by the underlying spot market price at a specific time point and the price evolution over time is assumed to be continuous. The former leads to a biased calculation of option payoff and the latter is invalid empirically for many online advertising slots. This paper addresses these two limitations by proposing a new advertising option pricing framework. First, the option payoff is calculated based on an average price over a specific future period. Therefore, the option becomes path-dependent. The average price is measured by the power mean, which contains several existing option payoff functions as its special cases. Second, jump-diffusion stochastic models are used to describe the movement of the underlying spot market price, which incorporate several important statistical properties including jumps and spikes, non-normality, and absence of autocorrelations. A general option pricing algorithm is obtained based on Monte Carlo simulation. In addition, an explicit pricing formula is derived for the case when the option payoff is based on the geometric mean. This pricing formula is also a generalized version of several other option pricing models discussed in related studies [1], [2], [3], [4], [5], [6].

Includes members:
  Member "risk aware dynamic reserve prices of programmatic guarantee in display advertising":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "combining guaranteed and spot markets in display advertising selling guaranteed page views with stochastic demand")
  Member "a dynamic pricing model for unifying programmatic guarantee and real time bidding in display advertising":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a multi agent reinforcement learning method for impression allocation in online display advertising")
  Member "a lattice framework for pricing display advertisement options with the stochastic volatility underlying model":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "combining guaranteed and spot markets in display advertising selling guaranteed page views with stochastic demand")
  Member "real time bidding for online advertising measurement and analysis":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "motiac multi objective actor critics for real time bidding")
  Member "multi keyword multi click advertisement option contracts for sponsored search":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "combining guaranteed and spot markets in display advertising selling guaranteed page views with stochastic demand")
  Member "shale an efficient algorithm for allocation of guaranteed display advertising":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "combining guaranteed and spot markets in display advertising selling guaranteed page views with stochastic demand")
  Member "sequential selection of correlated ads by pomdps":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "real time bidding campaigns optimization using attribute selection")

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)