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 "streaming weighted matchings optimal meets greedy"):
  Abstract: We consider the problem of approximating a maximum weighted matching, when the edges of an underlying weighted graph $G(V,E)$ are revealed in a streaming fashion. We analyze a variant of the previously best-known $(4+\epsilon)$-approximation algorithm due to Crouch and Stubbs (APPROX, 2014), and prove their conjecture that it achieves a tight approximation factor of $3.5+\epsilon$. #R##N#The algorithm splits the stream into substreams on which it runs a greedy maximum matching algorithm. At the end of the stream, the selected edges are given as input to an optimal maximum weighted matching algorithm. To analyze the approximation guarantee, we develop a novel charging argument in which we decompose the edges of a maximum weighted matching of $G$ into a few natural classes, and then charge them separately to the edges of the matching output by our algorithm.

Includes members:
  Member "the shortest augmenting paths for online matchings on trees":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "improved dynamic graph coloring")
  Member "the locality of distributed symmetry breaking":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "distributed maximum matching verification in congest")
  Member "maintaining approximate maximum weighted matching in fully dynamic graphs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "popular conjectures as a barrier for dynamic planar graph algorithms")
  Member "improved approximation guarantees for weighted matching in the semi streaming model":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "space efficient approximation to maximum matching size from uniform edge samples")
  Member "a near optimal sublinear time algorithm for approximating the minimum vertex cover size":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "complexity and efficient algorithms for data inconsistency evaluating and repairing")
  Member "weighted matching in the semi streaming model":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "two player hidden pointer chasing and multi pass lower bounds in turnstile streams")

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)