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: "faster random walks by rewiring online social networks on the fly"
  Abstract: Many online social networks feature restrictive web interfaces which only allow the query of a user's local neighborhood through the interface. To enable analytics over such an online social network through its restrictive web interface, many recent efforts reuse the existing Markov Chain Monte Carlo methods such as random walks to sample the social network and support analytics based on the samples. The problem with such an approach, however, is the large amount of queries often required (i.e., a long "mixing time") for a random walk to reach a desired (stationary) sampling distribution. #R##N#In this paper, we consider a novel problem of enabling a faster random walk over online social networks by "rewiring" the social network on-the-fly. Specifically, we develop Modified TOpology (MTO)-Sampler which, by using only information exposed by the restrictive web interface, constructs a "virtual" overlay topology of the social network while performing a random walk, and ensures that the random walk follows the modified overlay topology rather than the original one. We show that MTO-Sampler not only provably enhances the efficiency of sampling, but also achieves significant savings on query cost over real-world online social networks such as Google Plus, Epinion etc.

Connected through hyperedge HE-1 (induced by source paper "degree ranking using local information"):
  with members:
    - "a faster method to estimate closeness centrality ranking"
    - "ant inspired density estimation via random walks"
    - "sublinear time estimation of degree distribution moments the arboricity connection"
    - "rank me thou shalln t compare me"
    - "understanding spreading patterns on social networks based on network topology"
    - "estimating the degree centrality ranking of a node"
    - "walk not wait faster sampling over online social networks"
    - "real time enhanced random sampling of online social networks"

Connected through hyperedge HE-2 (induced by source paper "sampling online social networks by random walk with indirect jumps"):
  with members:
    - "inferring networks of substitutable and complementary products"
    - "leveraging history for faster sampling of online social networks"
    - "romantic partnerships and the dispersion of social ties a network analysis of relationship status on facebook"
    - "efficiently estimating motif statistics of large networks"
    - "triadic measures on graphs the power of wedge sampling"
    - "multigraph sampling of online social networks"
    - "estimating and sampling graphs with multidimensional random walks"

Connected through hyperedge HE-3 (induced by source paper "characterizing directed and undirected networks via multidimensional walks with jumps"):
  with members:
    - "estimating and sampling graphs with multidimensional random walks"

Connected through hyperedge HE-4 (induced by source paper "local rewiring algorithms to increase clustering and grow a small world"):
  with members:
    - "updating and downdating techniques for optimizing network communicability"
    - "social structure of facebook networks"

Connected through hyperedge HE-5 (induced by source paper "leveraging history for faster sampling of online social networks"):
  with members:
    - "defining and evaluating network communities based on ground truth"
    - "walking on a graph with a magnifying glass stratified sampling via weighted random walks"
    - "estimating and sampling graphs with multidimensional random walks"

Connected through hyperedge HE-6 (induced by source paper "design of efficient sampling methods on hybrid social affiliation networks"):
  with members:
    - "triadic measures on graphs the power of wedge sampling"
    - "twitter mood predicts the stock market"
    - "multigraph sampling of online social networks"
    - "estimating and sampling graphs with multidimensional random walks"

Connected through hyperedge HE-7 (induced by source paper "walk not wait faster sampling over online social networks"):
  with members:
    - "crawling facebook for social network analysis purposes"
    - "walking on a graph with a magnifying glass stratified sampling via weighted random walks"
    - "four degrees of separation"
    - "estimating and sampling graphs with multidimensional random walks"

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)