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: "counting hypergraphs in data streams"
  Abstract: We present the first streaming algorithm for counting an arbitrary hypergraph H of constant size in a massive hypergraph G. Our algorithm can handle both edge-insertions and edge-deletions, and is applicable for the distributed setting. Moreover, our approach provides the first family of graph polynomials for the hypergraph counting problem. Because of the close relationship between hypergraphs and set systems, our approach may have applications in studying similar problems.

Connected through hyperedge HE-1 (induced by source paper "better streaming algorithms for the maximum coverage problem"):
  with members:
    - "correlation clustering in data streams"
    - "tight space approximation tradeoff for the multi pass streaming set cover problem"
    - "almost optimal streaming algorithms for coverage problems"
    - "tight bounds for single pass streaming complexity of the set cover problem"
    - "towards tight bounds for the streaming set cover problem"
    - "densest subgraph in dynamic graph streams"
    - "streaming algorithms for submodular function maximization"
    - "incidence geometries and the pass complexity of semi streaming set cover"

Connected through hyperedge HE-2 (induced by source paper "kernelization via sampling with applications to dynamic graph streams"):
  with members:
    - "correlation clustering in data streams"
    - "densest subgraph in dynamic graph streams"
    - "tight bounds for linear sketches of approximate matchings"
    - "sublinear estimation of weighted matchings in dynamic data streams"
    - "maximum matching in turnstile streams"
    - "applications of uniform sampling densest subgraph and beyond"
    - "space and time efficient algorithm for maintaining dense subgraphs on one pass dynamic streams"
    - "sketching cuts in graphs and hypergraphs"

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)