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 "counting butterfies from a large bipartite graph stream"):
  Abstract: We consider the estimation of properties on massive bipartite graph streams, where each edge represents a connection between entities in two different partitions. We present sublinear-space one-pass algorithms for accurately estimating the number of butterflies in the graph stream. Our estimates have provable guarantees on their quality, and experiments show promising tradeoffs between space and accuracy. We also present extensions to sliding windows. While there are many works on counting subgraphs within unipartite graph streams, our work seems to be one of the few to effectively handle 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 "on sampling from massive graph streams":
    also connected through other hyperedges:
      - Hyperedge HE-2 (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-3 (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-4 (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-5 (induced by source paper "hypergraph motifs concepts algorithms and discoveries")
  Member "evolution of directed triangle motifs in the google osn":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "subgraph networks with application to structural feature space expansion")
  Member "path sampling a fast and provable method for estimating 4 vertex subgraph counts":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "the power of pivoting for exact clique counting")
  Member "triangle counting in dynamic graph streams":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "fleet butterfly estimation from a bipartite graph stream")

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)