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: "a new approach to online scheduling approximating the optimal competitive ratio"
  Abstract: We propose a new approach to competitive analysis in online scheduling by introducing the novel concept of competitive-ratio approximation schemes. Such a scheme algorithmically constructs an online algorithm with a competitive ratio arbitrarily close to the best possible competitive ratio for any online algorithm. We study the problem of scheduling jobs online to minimize the weighted sum of completion times on parallel, related, and unrelated machines, and we derive both deterministic and randomized algorithms which are almost best possible among all online algorithms of the respective settings. We also generalize our techniques to arbitrary monomial cost functions and apply them to the makespan objective. Our method relies on an abstract characterization of online algorithms combined with various simplifications and transformations. We also contribute algorithmic means to compute the actual value of the best possi- ble competitive ratio up to an arbitrary accuracy. This strongly contrasts all previous manually obtained competitiveness results for algorithms and, most importantly, it reduces the search for the optimal com- petitive ratio to a question that a computer can answer. We believe that our concept can also be applied to many other problems and yields a new perspective on online algorithms in general.

Connected through hyperedge HE-1 (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"
    - "online makespan minimization with parallel schedules"
    - "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"
    - "online bin packing with advice"

Connected through hyperedge HE-2 (induced by source paper "a competitive ratio approximation scheme for the k server problem in fixed finite metrics"):
  with members:
    - "competitive ratio approximation schemes for minimizing the makespan in the online list model"
    - "randomized online computation with high probability guarantees"
    - "a polylogarithmic competitive algorithm for the k server problem"
    - "ramsey type theorems for metric spaces with applications to online problems"
    - "better algorithms for unfair metrical task systems and applications"
    - "competitive paging algorithms"

Connected through hyperedge HE-3 (induced by source paper "competitive ratio approximation schemes for minimizing the makespan in the online list model"):
  with members:
    - "approximating the optimal competitive ratio for an ancient online scheduling problem"

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)