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: "online makespan minimization with parallel schedules"
  Abstract: In online makespan minimization a sequence of jobs $\sigma = J_1,..., J_n$ has to be scheduled on $m$ identical parallel machines so as to minimize the maximum completion time of any job. We investigate the problem with an essentially new model of resource augmentation. Here, an online algorithm is allowed to build several schedules in parallel while processing $\sigma$. At the end of the scheduling process the best schedule is selected. This model can be viewed as providing an online algorithm with extra space, which is invested to maintain multiple solutions. The setting is of particular interest in parallel processing environments where each processor can maintain a single or a small set of solutions. #R##N#We develop a $(4/3+\eps)$-competitive algorithm, for any $0<\eps\leq 1$, that uses a number of $1/\eps^{O(\log (1/\eps))}$ schedules. We also give a $(1+\eps)$-competitive algorithm, for any $0<\eps\leq 1$, that builds a polynomial number of $(m/\eps)^{O(\log (1/\eps) / \eps)}$ schedules. This value depends on $m$ but is independent of the input $\sigma$. The performance guarantees are nearly best possible. We show that any algorithm that achieves a competitiveness smaller than 4/3 must construct $\Omega(m)$ schedules. Our algorithms make use of novel guessing schemes that (1) predict the optimum makespan of a job sequence $\sigma$ to within a factor of $1+\eps$ and (2) guess the job processing times and their frequencies in $\sigma$. In (2) we have to sparsify the universe of all guesses so as to reduce the number of schedules to a constant. #R##N#The competitive ratios achieved using parallel schedules are considerably smaller than those in the standard problem without resource augmentation.

Connected through hyperedge HE-1 (induced by source paper "online scheduling with makespan minimization state of the art results research challenges and open problems"):
  with members:
    - "scheduling on two types of resources a survey"

Connected through hyperedge HE-2 (induced by source paper "parallel online algorithms for the bin packing problem"):
  with members:
    - "a new lower bound for classic online bin packing"
    - "a new and improved algorithm for online bin packing"
    - "beating the harmonic lower bound for online bin packing"
    - "online algorithms with advice for bin packing and scheduling problems"
    - "on the list update problem with advice"
    - "online bin packing with advice"

Connected through hyperedge HE-3 (induced by source paper "multi round cooperative search games with multiple players"):
  with members:
    - "the impact of local information on the performance of multiagent systems"
    - "the ants problem"
    - "bayesian incentive compatible bandit exploration"
    - "computer science and game theory a brief survey"
    - "a computer scientist looks at game theory"

Connected through hyperedge HE-4 (induced by source paper "cooperative search games symmetric equilibria robustness and price of anarchy"):
  with members:
    - "the impact of local information on the performance of multiagent systems"
    - "the ants problem"
    - "bayesian incentive compatible bandit exploration"
    - "computer science and game theory a brief survey"
    - "a computer scientist looks at game theory"

Connected through hyperedge HE-5 (induced by source paper "intense competition can drive selfish explorers to optimize coverage"):
  with members:
    - "the ants problem"
    - "bayesian incentive compatible bandit exploration"
    - "parallel exhaustive search without coordination"

Connected through hyperedge HE-6 (induced by source paper "weighted online problems with advice"):
  with members:
    - "on the power of advice and randomization for online bipartite matching"
    - "online bounded analysis"
    - "randomization can be as helpful as a glimpse of the future in online computation"
    - "online algorithms with advice for bin packing and scheduling problems"
    - "advice complexity of the online induced subgraph problem"

Connected through hyperedge HE-7 (induced by source paper "randomization can be as helpful as a glimpse of the future in online computation"):
  with members:
    - "on the power of advice and randomization for online bipartite matching"
    - "optimal online edge coloring of planar graphs with advice"
    - "online multi coloring with advice"
    - "on the list update problem with advice"
    - "a competitive ratio approximation scheme for the k server problem in fixed finite metrics"
    - "on advice complexity of the k server problem under sparse metrics"
    - "a new approach to online scheduling approximating the optimal competitive ratio"
    - "online bin packing with advice"

Connected through hyperedge HE-8 (induced by source paper "optimal online edge coloring of planar graphs with advice"):
  with members:
    - "online algorithms with advice for bin packing and scheduling problems"
    - "on the list update problem with advice"
    - "online bin packing with advice"

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)