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 "phase transitions and a model order selection criterion for spectral graph clustering"):
  Abstract: One of the longstanding open problems in spectral graph clustering (SGC) is the so-called model order selection problem: automated selection of the correct number of clusters. This is equivalent to the problem of finding the number of connected components or communities in an undirected graph. We propose automated model order selection (AMOS), a solution to the SGC model selection problem under a random interconnection model (RIM) using a novel selection criterion that is based on an asymptotic phase transition analysis. AMOS can more generally be applied to discovering hidden block diagonal structure in symmetric non-negative matrices. Numerical experiments on simulated graphs validate the phase transition analysis, and real-world network data is used to validate the performance of the proposed model selection procedure.

Includes members:
  Member "estimating the number of communities in a network":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "mean field theory of graph neural networks in graph partitioning")
  Member "spectral detection in the censored block model":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "spectral clustering of signed graphs via matrix power means")
  Member "universal phase transition in community detectability under a stochastic block model":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "multilayer spectral graph clustering via convex layer aggregation")
  Member "local set based graph signal reconstruction":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "graph signal processing part ii processing and analyzing signals on graphs")
  Member "incremental method for spectral clustering of increasing orders":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "temporal network representation learning")
  Member "signal recovery on graphs variation minimization":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "deep unsupervised learning of 3d point clouds via graph topology inference and filtering")
  Member "multi layer graph analysis for dynamic social networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "latent heterogeneous multilayer community detection")
  Member "exact recovery in the stochastic block model":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "renyi entropy bounds on the active learning cost performance tradeoff")

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)