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: "graph reconstruction via distance oracles"
  Abstract: We study the problem of reconstructing a hidden graph given access to a distance oracle. We design randomized algorithms for the following problems: reconstruction of a degree bounded graph with query complexity $\tilde{O}(n^{3/2})$; reconstruction of a degree bounded outerplanar graph with query complexity $\tilde{O}(n)$; and near-optimal approximate reconstruction of a general graph.

Connected through hyperedge HE-1 (induced by source paper "learning networks from random walk based node similarities"):
  with members:
    - "predicting positive and negative links with noisy queries theory practice"
    - "deepwalk online learning of social representations"
    - "near linear query complexity for graph inference"
    - "a tractable approach to finding closest truncated commute time neighbors in large graphs"
    - "fast incremental and personalized pagerank"
    - "hitting and commute times in large graphs are often misleading"

Connected through hyperedge HE-2 (induced by source paper "on the structure of unique shortest paths in graphs"):
  with members:
    - "towards improving brandes algorithm for betweenness centrality"
    - "linear size distance preservers"
    - "near linear query complexity for graph inference"
    - "faster all pairs shortest paths via circuit complexity"

Connected through hyperedge HE-3 (induced by source paper "computing exact minimum cuts without knowing the graph"):
  with members:
    - "a faster cutting plane method and its implications for combinatorial and convex optimization"
    - "on sketching quadratic forms"
    - "sketching cuts in graphs and hypergraphs"
    - "deterministic global minimum cut of a simple graph in near linear time"
    - "near linear query complexity for graph inference"
    - "efficient minimization of decomposable submodular functions"

Connected through hyperedge HE-4 (induced by source paper "near linear query complexity for graph inference"):
  with members:
    - "topology discovery of sparse random graphs with few participants"
    - "efficient measurement of complex networks using link queries"
    - "exploring networks with traceroute like probes theory and simulations"

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.DS(Data Structures and Algorithms)