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: "ad serving using a compact allocation plan"
  Abstract: A large fraction of online display advertising is sold via guaranteed contracts: a publisher guarantees to the advertiser a certain number of user visits satisfying the targeting predicates of the contract. The publisher is then tasked with solving the ad serving problem - given a user visit, which of the thousands of matching contracts should be displayed, so that by the expiration time every contract has obtained the requisite number of user visits. The challenges of the problem come from (1) the sheer size of the problem being solved, with tens of thousands of contracts and billions of user visits, (2) the unpredictability of user behavior, since these contracts are sold months ahead of time, when only a forecast of user visits is available and (3) the minute amount of resources available online, as an ad server must respond with a matching contract in a fraction of a second. #R##N#We present a solution to the guaranteed delivery ad serving problem using {\em compact allocation plans}. These plans, computed offline, can be efficiently queried by the ad server during an ad call; they are small, using only O(1) space for contract; and are stateless, allowing for distributed serving without any central coordination. We evaluate this approach on a real set of user visits and guaranteed contracts and show that the compact allocation plans are an effective way of solving the guaranteed delivery ad serving problem.

Connected through hyperedge HE-1 (induced by source paper "optimal delivery with budget constraint in e commerce advertising"):
  with members:
    - "near optimal online algorithms and fast approximation algorithms for resource allocation problems"
    - "smart pacing for effective online ad campaign optimization"
    - "real time bid optimization with smooth budget delivery in online advertising"

Connected through hyperedge HE-2 (induced by source paper "efficient delivery policy to minimize user traffic consumption in guaranteed advertising"):
  with members:
    - "a dynamic pricing model for unifying programmatic guarantee and real time bidding in display advertising"
    - "shale an efficient algorithm for allocation of guaranteed display advertising"
    - "bidding for representative allocations for display advertising"
    - "online stochastic matching beating 1 1 e"

Connected through hyperedge HE-3 (induced by source paper "fast algorithms for online stochastic convex programming"):
  with members:
    - "near optimal online algorithms and fast approximation algorithms for resource allocation problems"
    - "bandits with concave rewards and convex knapsacks"
    - "how the experts algorithm can help solve lps online"
    - "a near optimal dynamic learning algorithm for online matching problems with concave returns"
    - "bandits with knapsacks"
    - "dynamic pricing with limited supply"
    - "online vertex weighted bipartite matching and single bid budgeted allocations"
    - "online stochastic matching online actions based on offline statistics"

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.DS(Data Structures and Algorithms)