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: "the frequent items problem in online streaming under various performance measures"
  Abstract: In this paper, we strengthen the competitive analysis results obtained for a fundamental online streaming problem, the Frequent Items Problem. Additionally, we contribute with a more detailed analysis of this problem, using alternative performance measures, supplementing the insight gained from competitive analysis. The results also contribute to the general study of performance measures for online algorithms. It has long been known that competitive analysis suffers from drawbacks in certain situations, and many alternative measures have been proposed. However, more systematic comparative studies of performance measures have been initiated recently, and we continue this work, using competitive analysis, relative interval analysis, and relative worst order analysis on the Frequent Items Problem.

Connected through hyperedge HE-1 (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"
    - "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"
    - "a comparison of performance measures for online algorithms"

Connected through hyperedge HE-2 (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"
    - "superiority of exact quantum automata for promise problems"
    - "a comparison of performance measures for online algorithms"

Connected through hyperedge HE-3 (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"

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)