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: "structural sparsity of complex networks bounded expansion in random models and real world graphs"
  Abstract: This research establishes that many real-world networks exhibit bounded expansion, a strong notion of structural sparsity, and demonstrates that it can be leveraged to design efficient algorithms for network analysis. We analyze several common network models regarding their structural sparsity. We show that, with high probability, (1) graphs sampled with a prescribed s parse degree sequence; (2) perturbed bounded-degree graphs; (3) stochastic block models with small probabilities; result in graphs of bounded expansion. #R##N#In contrast, we show that the Kleinberg and the Barabasi-Albert model have unbounded expansion. We support our findings with empirical measurements on a corpus of real-world networks.

Connected through hyperedge HE-1 (induced by source paper "a color avoiding approach to subgraph counting in bounded expansion classes"):
  with members:
    - "empirical evaluation of approximation algorithms for generalized graph coloring and uniform quasi wideness"
    - "experimental evaluation of counting subgraph isomorphisms in classes of bounded expansion"
    - "a dynamic data structure for counting subgraphs in sparse graphs"
    - "listing all maximal cliques in sparse graphs in near optimal time"

Connected through hyperedge HE-2 (induced by source paper "distributed domination on graph classes of bounded expansion"):
  with members:
    - "the generalised colouring numbers on classes of bounded expansion"
    - "on the complexity of local distributed graph problems"
    - "approximation algorithms for polynomial expansion and low density graphs"
    - "cops robbers and threatening skeletons padded decomposition for minor free graphs"
    - "deciding first order properties of nowhere dense graphs"
    - "analytical approach to parallel repetition"
    - "local computation lower and upper bounds"
    - "a distributed algorithm to find k dominating sets"

Connected through hyperedge HE-3 (induced by source paper "characterising bounded expansion by neighbourhood complexity"):
  with members:
    - "bidimensionality and kernels"
    - "kernelization and sparseness the case of dominating set"
    - "kernelization using structural parameters on sparse graph classes"
    - "deciding first order properties of nowhere dense graphs"
    - "kernels for connected dominating set on graphs with excluded topological subgraphs"
    - "linear kernels and single exponential algorithms via protrusion decompositions"
    - "structure theorem and isomorphism test for graphs with excluded topological subgraphs"
    - "homomorphism preservation on quasi wide classes"

Connected through hyperedge HE-4 (induced by source paper "fast counting of medium sized rooted subgraphs"):
  with members:
    - "counting triangles in massive graphs with mapreduce"
    - "path sampling a fast and provable method for estimating 4 vertex subgraph counts"
    - "the challenges of unbounded treewidth in parameterised subgraph counting problems"
    - "spectral redemption in clustering sparse networks"
    - "counting thin subgraphs via packings faster than meet in the middle time"

Connected through hyperedge HE-5 (induced by source paper "hyperbolicity degeneracy and expansion of random intersection graphs"):
  with members:
    - "connectivity in secure wireless sensor networks under transmission constraints"
    - "on the strengths of connectivity and robustness in general random intersection graphs"
    - "on the hyperbolicity of small world and tree like random graphs"

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)