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: "evolution of the internet k dense structure"
  Abstract: As the Internet autonomous system (AS)-level topology grows over time, some of its structural properties remain unchanged. Such time-invariant properties are generally interesting because they tend to reflect some fundamental processes or constraints behind Internet growth. As has been shown before, the time-invariant structural properties of the Internet include some most basic ones, such as the degree distribution or clustering. Here, we add to this time-invariant list a nontrivial property—  $k$   -dense decomposition. This property is derived from a recursive form of edge multiplicity, defined as the number of triangles that share a given edge. We show that after proper normalization, the    $k$  -dense decomposition of the Internet has remained stable over the last decade, even though the Internet size has approximately doubled, and so has the   $k$   -density of its   $k$   -densest core. This core consists mostly of content providers peering at Internet eXchange Points, and it only loosely overlaps with the high-degree or high-rank AS core, consisting mostly of tier-1 transit providers. We thus show that high degrees and high   $k$   -densities reflect two different Internet-specific properties of ASs (transit versus content providers). As a consequence, even though degrees and   $k$  -densities of nodes are correlated, the relative fluctuations are strong, and related to that, random graphs with the same degree distribution or even degree correlations as in the Internet, do not reproduce its   $k$  -dense decomposition. Therefore an interesting open question is what Internet topology models or generators can fully explain or at least reproduce the   $k$   -dense properties of the Internet.

Connected through hyperedge HE-1 (induced by source paper "hierarchical decomposition mechanism by konig egervary layer subgraph with application on vertex cover"):
  with members:
    - "core influence mechanism on vertex cover problem through leaf removal core breaking"
    - "modeling polypharmacy side effects with graph convolutional networks"
    - "higher order organization of complex networks"
    - "finding perfect matchings in bipartite hypergraphs"
    - "research on solution space of bipartite graph vertex cover by maximum matchings"
    - "threshold values of random k sat from the cavity method"

Connected through hyperedge HE-2 (induced by source paper "the devils in the details placing decoy routers in the internet"):
  with members:
    - "few throats to choke on the current structure of the internet"
    - "isolario a do ut des approach to improve the appeal of bgp route collecting"

Connected through hyperedge HE-3 (induced by source paper "exploring the node importance based on von neumann entropy"):
  with members:
    - "modeling polypharmacy side effects with graph convolutional networks"

Connected through hyperedge HE-4 (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"
    - "truss decomposition in massive networks"
    - "social structure of facebook networks"
    - "a model of internet topology using k shell decomposition"
    - "k core decomposition of internet graphs hierarchies self similarity and measurement biases"
    - "an o m algorithm for cores decomposition of networks"

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.SI(Social and Information Networks)