human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "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.

Connected through hyperedge HE-1 (induced by source paper "building large k cores from sparse graphs"):
  with members:
    - "a survey of parameterized algorithms and the complexity of edge modification"
    - "finding even subgraphs even faster"
    - "editing to a connected graph of given degrees"
    - "preventing unraveling in social networks gets harder"
    - "parameterized complexity of the anchored k core problem for directed graphs"
    - "editing to a graph of given degrees"
    - "understanding edge connectivity in the internet through core decomposition"

Connected through hyperedge HE-2 (induced by source paper "anatomy of an online misinformation network"):
  with members:
    - "the spread of low credibility content by social bots"
    - "how algorithmic popularity bias hinders or promotes quality"
    - "disinformation and social bot operations in the run up to the 2017 french presidential election"
    - "early detection of promoted campaigns on social media"
    - "limited individual attention and online virality of low quality information"
    - "online human bot interactions detection estimation and characterization"
    - "hoaxy a platform for tracking online misinformation"
    - "botornot a system to evaluate social bots"

Connected through hyperedge HE-3 (induced by source paper "an experimental survey on big data frameworks"):
  with members:
    - "bladyg a graph processing framework for large dynamic graphs"
    - "mr simlab scalable subgraph selection with label similarity for big data"
    - "big graph mining frameworks and techniques"
    - "a tale of two data intensive paradigms applications abstractions and architectures"
    - "mli an api for distributed machine learning"

Connected through hyperedge HE-4 (induced by source paper "social centrality using network hierarchy and community structure"):
  with members:
    - "centrality measures for networks with community structure"
    - "labelrank a stabilized label propagation algorithm for community detection in networks"
    - "axioms for centrality"
    - "truss decomposition in massive networks"

Connected through hyperedge HE-5 (induced by source paper "bladyg a graph processing framework for large dynamic graphs"):
  with members:
    - "big graph mining frameworks and techniques"

Connected through hyperedge HE-6 (induced by source paper "fast hierarchy construction for dense subgraphs"):
  with members:
    - "i o efficient core graph decomposition at web scale"
    - "locally estimating core numbers"
    - "evolution of the internet k dense structure"
    - "truss decomposition in massive networks"
    - "social structure of facebook networks"
    - "a model of internet topology using k shell decomposition"
    - "an o m algorithm for cores decomposition of networks"

Connected through hyperedge HE-7 (induced by source paper "asymptotic analysis of equivalences and core structures in kronecker style graph models"):
  with members:
    - "hyperbolicity degeneracy and expansion of random intersection graphs"
    - "core periphery structure in networks"
    - "the similarity between stochastic kronecker and chung lu graph models"
    - "community structure in large networks natural cluster sizes and the absence of large well defined clusters"
    - "a model of internet topology using k shell decomposition"

Connected through hyperedge HE-8 (induced by source paper "big data frameworks a comparative study"):
  with members:
    - "bladyg a graph processing framework for large dynamic graphs"
    - "mr simlab scalable subgraph selection with label similarity for big data"
    - "big graph mining frameworks and techniques"
    - "a tale of two data intensive paradigms applications abstractions and architectures"
    - "mli an api for distributed machine learning"

Question: Please tell me which class the center node 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)