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: "universal emergence of pagerank"
  Abstract: The PageRank algorithm enables us to rank the nodes of a network through a specific eigenvector of the Google matrix, using a damping parameter α ∈ ]0, 1[. Using extensive numerical simulations of large web networks, with a special accent on British University networks, we determine numerically and analytically the universal features of the PageRank vector at its emergence when α → 1. The whole network can be divided into a core part and a group of invariant subspaces. For α → 1, PageRank converges to a universal power-law distribution on the invariant subspaces whose size distribution also follows a universal power law. The convergence of PageRank at α → 1 is controlled by eigenvalues of the core part of the Google matrix, which are extremely close to unity, leading to large relaxation times as, for example, in spin glasses.

Connected through hyperedge HE-1 (induced by source paper "google matrix of bitcoin network"):
  with members:
    - "bitcoin transaction graph analysis"
    - "deanonymisation of clients in bitcoin p2p network"
    - "spectral properties of google matrix of wikipedia and other networks"
    - "pagerank of integers"
    - "towards physical laws for software architecture"
    - "google matrix and ulam networks of intermittency maps"

Connected through hyperedge HE-2 (induced by source paper "wikipedia mining of hidden links between political leaders"):
  with members:
    - "wikipedia ranking of world universities"
    - "interactions of cultures and top people of wikipedia from ranking of 24 language editions"
    - "spectral properties of google matrix of wikipedia and other networks"
    - "highlighting entanglement of cultures via ranking of multilingual wikipedia articles"
    - "biographical social networks on wikipedia a cross cultural study of links that made history"
    - "towards physical laws for software architecture"
    - "two dimensional ranking of wikipedia articles"

Connected through hyperedge HE-3 (induced by source paper "google matrix of twitter"):
  with members:
    - "pagerank of integers"
    - "toward two dimensional search engines"
    - "fractal weyl law for linux kernel architecture"
    - "four degrees of separation"
    - "towards physical laws for software architecture"
    - "two dimensional ranking of wikipedia articles"
    - "google matrix and ulam networks of intermittency maps"
    - "google matrix dynamical attractors and ulam 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.IR(Information Retrieval)