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: "two betweenness centrality measures based on randomized shortest paths"
  Abstract: This paper introduces two new closely related betweenness centrality measures based on the Randomized Shortest Paths (RSP) framework, which fill a gap between traditional network centrality measures based on shortest paths and more recent methods considering random walks or current flows. The framework defines Boltzmann probability distributions over paths of the network which focus on the shortest paths, but also take into account longer paths depending on an inverse temperature parameter. RSP’s have previously proven to be useful in defining distance measures on networks. In this work we study their utility in quantifying the importance of the nodes of a network. The proposed RSP betweenness centralities combine, in an optimal way, the ideas of using the shortest and purely random paths for analysing the roles of network nodes, avoiding issues involving these two paradigms. We present the derivations of these measures and how they can be computed in an efficient way. In addition, we show with real world examples the potential of the RSP betweenness centralities in identifying interesting nodes of a network that more traditional methods might fail to notice.

Connected through hyperedge HE-1 (induced by source paper "covariance and correlation kernels on a graph in the generalized bag of paths formalism"):
  with members:
    - "randomized optimal transport on a graph framework and new distance measures"
    - "network representation learning a survey"
    - "a bag of paths node criticality measure"
    - "a comprehensive survey of graph embedding problems techniques and applications"
    - "semantic similarity from natural language and ontology analysis"
    - "deepwalk online learning of social representations"
    - "distributed representations of words and phrases and their compositionality"
    - "interpolating between random walks and shortest paths a path functional approach"

Connected through hyperedge HE-2 (induced by source paper "randomized shortest paths with net flows and capacity constraints"):
  with members:
    - "randomized optimal transport on a graph framework and new distance measures"
    - "interpolating between random walks and shortest paths a path functional approach"
    - "nearly linear time algorithms for graph partitioning graph sparsification and solving linear systems"
    - "objective criteria for the evaluation of clustering methods"

Connected through hyperedge HE-3 (induced by source paper "a constrained randomized shortest paths framework for optimal exploration"):
  with members:
    - "a unified view of entropy regularized markov decision processes"
    - "an alternative softmax operator for reinforcement learning"
    - "g learning taming the noise in reinforcement learning via soft updates"
    - "interpolating between random walks and shortest paths a path functional approach"
    - "dynamic policy programming"

Connected through hyperedge HE-4 (induced by source paper "randomized optimal transport on a graph framework and new distance measures"):
  with members:
    - "a bag of paths node criticality measure"
    - "optimal transport for domain adaptation"
    - "regularized discrete optimal transport"
    - "interpolating between random walks and shortest paths a path functional approach"

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)