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 "fleet butterfly estimation from a bipartite graph stream"):
  Abstract: We consider space-efficient single-pass estimation of the number of butterflies, a fundamental bipartite graph motif, from a massive bipartite graph stream where each edge represents a connection between entities in two different partitions. We present a space lower bound for any streaming algorithm that can estimate the number of butterflies accurately, as well as FLEET, a suite of algorithms for accurately estimating the number of butterflies in the graph stream. Estimates returned by the algorithms come with provable guarantees on the approximation error, and experiments show good tradeoffs between the space used and the accuracy of approximation. We also present space-efficient algorithms for estimating the number of butterflies within a sliding window of the most recent elements in the stream. While there is a significant body of work on counting subgraphs such as triangles in a unipartite graph stream, our work seems to be one of the few to tackle the case of bipartite graph streams.

Includes members:
  Member "parallel algorithms for butterfly computations":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "efficient bitruss decomposition for large scale bipartite graphs")
  Member "vertex priority based butterfly counting for large scale bipartite networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "efficient bitruss decomposition for large scale bipartite graphs")
  Member "butterfly counting in bipartite networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "hypergraph motifs concepts algorithms and discoveries")
  Member "edge sample and discard a new algorithm for counting triangles in large dynamic graphs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on counting triangles through edge sampling in large dynamic graphs")
  Member "on sampling from massive graph streams":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "hypergraph motifs concepts algorithms and discoveries")
  Member "peeling bipartite networks for dense subgraph discovery":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "efficient bitruss decomposition for large scale bipartite graphs")
  Member "escape efficiently counting all 5 vertex subgraphs":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "hypergraph motifs concepts algorithms and discoveries")
  Member "measuring and modeling bipartite graphs with community structure":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "hypergraph motifs concepts algorithms and discoveries")

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)