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: "algorithmic methods for sponsored search advertising"
  Abstract: Modern commercial Internet search engines display advertisements along side the search results in response to user queries. Such sponsored search relies on market mechanisms to elicit prices for these advertisements, making use of an auction among advertisers who bid in order to have their ads shown for specific keywords. We present an overview of the current systems for such auctions and also describe the underlying game-theoretic aspects. The game involves three parties--advertisers, the search engine, and search users--and we present example research directions that emphasize the role of each. The algorithms for bidding and pricing in these games use techniques from three mathematical areas: mechanism design, optimization, and statistical estimation. Finally, we present some challenges in sponsored search advertising.

Connected through hyperedge HE-1 (induced by source paper "aiads automated and intelligent advertising system for sponsored search"):
  with members:
    - "deep reinforcement learning for sponsored search real time bidding"
    - "beyond keywords and relevance a personalized ad retrieval framework in e commerce sponsored search"
    - "roi constrained auctions"
    - "optimized cost per click in taobao display advertising"
    - "sponsored search auctions with rich ads"
    - "mechanism design for value maximizers"
    - "scalable semantic matching of queries to ads in sponsored search advertising"
    - "fast core pricing for rich advertising auctions"

Connected through hyperedge HE-2 (induced by source paper "online submodular maximization under a matroid constraint with application to learning assignments"):
  with members:
    - "learning policies for contextual submodular prediction"
    - "online learning of assignments that maximize submodular functions"
    - "sponsored search auctions with markovian users"

Connected through hyperedge HE-3 (induced by source paper "general truthfulness characterizations via convex analysis"):
  with members:
    - "the lovasz bregman divergence and connections to rank aggregation clustering and web ranking"
    - "designing markets for daily deals"
    - "efficiency revenue trade offs in auctions"
    - "approaching utopia strong truthfulness and externality resistant mechanisms"
    - "eliciting forecasts from self interested experts scoring rules for decision makers"
    - "a new understanding of prediction markets via no regret learning"
    - "statistical exponential families a digest with flash cards"
    - "characterizing truthful multi armed bandit mechanisms"

Connected through hyperedge HE-4 (induced by source paper "online advertisement optimization and stochastic networks"):
  with members:
    - "online stochastic packing applied to display ad allocation"
    - "optimal scheduling for fair resource allocation in ad hoc networks with elastic and inelastic traffic"
    - "a dynamic near optimal algorithm for online linear programming"
    - "characterizing optimal adword auctions"

Connected through hyperedge HE-5 (induced by source paper "online learning of assignments that maximize submodular functions"):
  with members:
    - "sponsored search auctions with markovian users"

Connected through hyperedge HE-6 (induced by source paper "sponsored search auctions with markovian users"):
  with members:
    - "a truthful mechanism for offline ad slot scheduling"
    - "budget optimization in search based advertising auctions"
    - "stochastic models for budget optimization in search based advertising"

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)