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 comparison of performance measures for online algorithms"
  Abstract: This paper provides a systematic study of several proposed measures for online algorithms in the context of a specific problem, namely, the two server problem on three colinear points. Even though the problem is simple, it encapsulates a core challenge in online algorithms which is to balance greediness and adaptability. We examine Competitive Analysis, the Max/Max Ratio, the Random Order Ratio, Bijective Analysis and Relative Worst Order Analysis, and determine how these measures compare the Greedy Algorithm, Double Coverage, and Lazy Double Coverage, commonly studied algorithms in the context of server problems. We find that by the Max/Max Ratio and Bijective Analysis, Greedy is the best of the three algorithms. Under the other measures, Double Coverage and Lazy Double Coverage are better, though Relative Worst Order Analysis indicates that Greedy is sometimes better. Only Bijective Analysis and Relative Worst Order Analysis indicate that Lazy Double Coverage is better than Double Coverage. Our results also provide the first proof of optimality of an algorithm under Relative Worst Order Analysis.

Connected through hyperedge HE-1 (induced by source paper "benchmark design and prior independent optimization"):
  with members:
    - "an end to end argument in mechanism design prior independent auctions for budgeted agents"
    - "randomization beats second price as a prior independent auction"
    - "optimal auctions vs anonymous pricing"
    - "a simple and approximately optimal mechanism for an additive buyer"
    - "optimal competitive auctions"
    - "optimal platform design"
    - "envy freedom and prior free mechanism design"
    - "optimal mechansim design and money burning"

Connected through hyperedge HE-2 (induced by source paper "relative worst order analysis a survey"):
  with members:
    - "stochastic dominance and the bijective ratio of online algorithms"
    - "online bounded analysis"
    - "probabilistic analysis of the dual next fit algorithm for bin covering"
    - "relative interval analysis of paging algorithms on access graphs"
    - "the frequent items problem in online streaming under various performance measures"
    - "access graphs results for lru versus fifo under relative worst order analysis"
    - "a comparison of performance measures via online search"
    - "list factoring and relative worst order analysis"

Connected through hyperedge HE-3 (induced by source paper "quantum online streaming algorithms with constant number of advice bits"):
  with members:
    - "quantum online algorithms with respect to space complexity"
    - "quantum versus classical online streaming algorithms with logarithmic size of memory"
    - "exact affine obdds"
    - "reordering method and hierarchies for quantum and classical ordered binary decision diagrams"
    - "very narrow quantum obdds and width hierarchies for classical obdds"
    - "the frequent items problem in online streaming under various performance measures"
    - "superiority of exact quantum automata for promise problems"

Connected through hyperedge HE-4 (induced by source paper "quantum versus classical online streaming algorithms with logarithmic size of memory"):
  with members:
    - "quantum online algorithms with respect to space complexity"
    - "lower bound and hierarchies for quantum ordered read k times branching programs"
    - "exact affine obdds"
    - "reordering method and hierarchies for quantum and classical ordered binary decision diagrams"
    - "nondeterministic unitary obdds"
    - "automata and quantum computing"
    - "unary probabilistic and quantum automata on promise problems"
    - "very narrow quantum obdds and width hierarchies for classical obdds"

Connected through hyperedge HE-5 (induced by source paper "stochastic dominance and the bijective ratio of online algorithms"):
  with members:
    - "relative worst order analysis a survey"
    - "an optimal randomized online algorithm for reordering buffer management"
    - "on line file caching"
    - "on line paging against adversarially biased random inputs"
    - "the k server dual and loose competitiveness for paging"

Connected through hyperedge HE-6 (induced by source paper "relative interval analysis of paging algorithms on access graphs"):
  with members:
    - "access graphs results for lru versus fifo under relative worst order analysis"
    - "list factoring and relative worst order analysis"
    - "on line paging against adversarially biased random inputs"
    - "truly online paging with locality of reference"
    - "the k server dual and loose competitiveness for paging"

Connected through hyperedge HE-7 (induced by source paper "online bin covering expectations vs guarantees"):
  with members:
    - "relative interval analysis of paging algorithms on access graphs"
    - "access graphs results for lru versus fifo under relative worst order analysis"
    - "a comparison of performance measures via online search"
    - "list factoring and relative worst order analysis"

Connected through hyperedge HE-8 (induced by source paper "the frequent items problem in online streaming under various performance measures"):
  with members:
    - "relative interval analysis of paging algorithms on access graphs"
    - "access graphs results for lru versus fifo under relative worst order analysis"
    - "a comparison of performance measures via online search"

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)