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: "near linear query complexity for graph inference"
  Abstract: How efficiently can we find an unknown graph using distance or shortest path queries between its vertices? Let $G = (V,E)$ be an unweighted, connected graph of bounded degree. The edge set $E$ is initially unknown, and the graph can be accessed using a \emph{distance oracle}, which receives a pair of vertices $(u,v)$ and returns the distance between $u$ and $v$. In the \emph{verification} problem, we are given a hypothetical graph $\hat G = (V,\hat E)$ and want to check whether $G$ is equal to $\hat G$. We analyze a natural greedy algorithm and prove that it uses $n^{1+o(1)}$ distance queries. In the more difficult \emph{reconstruction} problem, $\hat G$ is not given, and the goal is to find the graph $G$. If the graph can be accessed using a \emph{shortest path oracle}, which returns not just the distance but an actual shortest path between $u$ and $v$, we show that extending the idea of greedy gives a reconstruction algorithm that uses $n^{1+o(1)}$ shortest path queries. When the graph has bounded treewidth, we further bound the query complexity of the greedy algorithms for both problems by $\tilde O(n)$. When the graph is chordal, we provide a randomized algorithm for reconstruction using $\tilde O(n)$ distance queries.

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"
    - "graph reconstruction via distance oracles"
    - "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"
    - "faster all pairs shortest paths via circuit complexity"
    - "graph reconstruction via distance oracles"

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"
    - "graph reconstruction via distance oracles"
    - "efficient minimization of decomposable submodular functions"

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)