human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "sublinear estimation of weighted matchings in dynamic data streams"):
  Abstract: This paper presents an algorithm for estimating the weight of a maximum weighted matching by augmenting any estimation routine for the size of an unweighted matching. The algorithm is implementable in any streaming model including dynamic graph streams. We also give the first constant estimation for the maximum matching size in a dynamic graph stream for planar graphs (or any graph with bounded arboricity) using $\tilde{O}(n^{4/5})$ space which also extends to weighted matching. Using previous results by Kapralov, Khanna, and Sudan (2014) we obtain a $\mathrm{polylog}(n)$ approximation for general graphs using $\mathrm{polylog}(n)$ space in random order streams, respectively. In addition, we give a space lower bound of $\Omega(n^{1-\varepsilon})$ for any randomized algorithm estimating the size of a maximum matching up to a $1+O(\varepsilon)$ factor for adversarial streams.

Includes members:
  Member "kernelization via sampling with applications to dynamic graph streams":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the sketching complexity of graph and hypergraph counting")
  Member "tight bounds for linear sketches of approximate matchings":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the sketching complexity of graph and hypergraph counting")
  Member "maximum matching in turnstile streams":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "two player hidden pointer chasing and multi pass lower bounds in turnstile streams")
  Member "better bounds for matchings in the streaming model":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "two player hidden pointer chasing and multi pass lower bounds in turnstile streams")
  Member "improved bounds for online preemptive matching":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "prophet inequality for bipartite matching merits of being simple and non adaptive")
  Member "maximum matching in semi streaming with few passes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "polynomial pass lower bounds for graph streaming algorithms")
  Member "improved approximation guarantees for weighted matching in the semi streaming model":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "space efficient approximation to maximum matching size from uniform edge samples")
  Member "graph sparsification in the semi streaming model":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "practice of streaming and dynamic graphs concepts models systems and parallelism")

Question: Please tell me which class the source paper 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)