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 "display advertising with real time bidding rtb and behavioural targeting"):
  Abstract: The most significant progress in recent years in online display advertising is what is known as the Real-Time Bidding (RTB) mechanism to buy and sell ads. RTB essentially facilitates buying an individual ad impression in real time while it is still being generated from a user's visit. RTB not only scales up the buying process by aggregating a large amount of available inventories across publishers but, most importantly, enables direct targeting of individual users. As such, RTB has fundamentally changed the landscape of digital marketing. Scientifically, the demand for automation, integration and optimisation in RTB also brings new research opportunities in information retrieval, data mining, machine learning and other related fields. In this monograph, an overview is given of the fundamental infrastructure, algorithms, and technical solutions of this new frontier of computational advertising. The covered topics include user response prediction, bid landscape forecasting, bidding algorithms, revenue optimisation, statistical arbitrage, dynamic pricing, and ad fraud detection.

Includes members:
  Member "neural feature embedding for user response prediction in real time bidding rtb":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "real time bidding campaigns optimization using attribute selection")
  Member "optimal real time bidding frameworks discussion":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "budget constrained bidding by model free reinforcement learning in display advertising")
  Member "product based neural networks for user response prediction":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "autoemb automated embedding dimensionality search in streaming recommendations")
  Member "lift based bidding in ad selection":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "learning multi touch conversion attribution with dual attention mechanisms for online advertising")
  Member "statistical arbitrage mining for display advertising":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "bidding machine learning to bid for directly optimizing profits in display advertising")
  Member "an empirical study on display ad impression viewability measurements":
    also connected through other hyperedges:
      (none)
  Member "real time bidding benchmarking with ipinyou dataset":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "scalable bid landscape forecasting in real time bidding")
  Member "neural machine translation by jointly learning to align and translate":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "chameleon a deep learning meta architecture for news recommender systems phd thesis")

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)