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 "approximate integration of streaming data"):
  Abstract: We approximate analytic queries on streaming data with a weighted reservoir sampling. For a stream of tuples of a Datawarehouse we show how to approximate some OLAP queries. For a stream of graph edges from a Social Network, we approximate the communities as the large connected components of the edges in the reservoir. We show that for a model of random graphs which follow a power law degree distribution, the community detection algorithm is a good approximation. Given two streams of graph edges from two Sources, we define the {\em Community Correlation} as the fraction of the nodes in communities in both streams. Although we do not store the edges of the streams, we can approximate the Community Correlation and define the {\em Integration of two streams}. We illustrate this approach with Twitter streams, associated with TV programs.

Includes members:
  Member "fully dynamic approximate maximum matching and minimum vertex cover in o log 3 n worst case update time":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "coarse grained complexity for dynamic algorithms")
  Member "network sampling from static to streaming graphs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "understanding the limitations of network online learning")

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.SI(Social and Information Networks)