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 "on counting triangles through edge sampling in large dynamic graphs"):
  Abstract: Traditional frameworks for dynamic graphs have relied on processing only the stream of edges added into or deleted from an evolving graph, but not any additional related information such as the degrees or neighbor lists of nodes incident to the edges. In this paper, we propose a new edge sampling framework for big-graph analytics in dynamic graphs which enhances the traditional model by enabling the use of additional related information. To demonstrate the advantages of this framework, we present a new sampling algorithm, called Edge Sample and Discard (ESD). It generates an unbiased estimate of the total number of triangles, which can be continuously updated in response to both edge additions and deletions. We provide a comparative analysis of the performance of ESD against two current state-of-the-art algorithms in terms of accuracy and complexity. The results of the experiments performed on real graphs show that, with the help of the neighborhood information of the sampled edges, the accuracy achieved by our algorithm is substantially better. We also characterize the impact of properties of the graph on the performance of our algorithm by testing on several Barabasi-Albert graphs.

Includes members:
  Member "edge sample and discard a new algorithm for counting triangles in large dynamic graphs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "fleet butterfly estimation from a bipartite graph stream")
  Member "edge based wedge sampling to estimate triangle counts in very large graphs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "retrieving top weighted triangles in graphs")
  Member "wrs waiting room sampling for accurate triangle counting in real graph streams":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "hypergraph motifs concepts algorithms and discoveries")
  Member "graph sample and hold a framework for big graph analytics":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "deep graph similarity learning a survey")
  Member "efficient triangle counting in large graphs via degree based vertex partitioning":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "parallel algorithms for small subgraph counting")
  Member "colorful triangle counting and a mapreduce implementation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "parallel algorithms for small subgraph counting")

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)