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 "k core decomposition of internet graphs hierarchies self similarity and measurement biases"):
  Abstract: We consider the $k$-core decomposition of network models and Internet graphs at the autonomous system (AS) level. The $k$-core analysis allows to characterize networks beyond the degree distribution and uncover structural properties and hierarchies due to the specific architecture of the system. We compare the $k$-core structure obtained for AS graphs with those of several network models and discuss the differences and similarities with the real Internet architecture. The presence of biases and the incompleteness of the real maps are discussed and their effect on the $k$-core analysis is assessed with numerical experiments simulating biased exploration on a wide range of network models. We find that the $k$-core analysis provides an interesting characterization of the fluctuations and incompleteness of maps as well as information helping to discriminate the original underlying structure.

Includes members:
  Member "a model of internet topology using k shell decomposition":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "target privacy preserving for social networks")
  Member "what is the real size of a sampled network the case of the internet":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "inferring structural characteristics of networks with strong and weak ties from fixed choice surveys")
  Member "systematic topology analysis and generation using degree correlations":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "recent advances in scalable network generation")
  Member "exploring networks with traceroute like probes theory and simulations":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "router level community structure of the internet autonomous systems")
  Member "k core decomposition a tool for the visualization of large scale networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a socio informatic approach to automated account classification on social media")
  Member "lessons from three views of the internet topology":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "performance of local information based link prediction a sampling perspective")
  Member "dimes let the internet measure itself":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "big data for traffic monitoring and management")
  Member "an o m algorithm for cores decomposition of networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "fastgae fast scalable and effective graph autoencoders with stochastic subgraph decoding")

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.NI(Networking and Internet Architecture)