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: "a note on distance labeling in planar graphs"
  Abstract: A distance labeling scheme is an assignments of labels, that is binary strings, to all nodes of a graph, so that the distance between any two nodes can be computed from their labels and the labels are as short as possible. A major open problem is to determine the complexity of distance labeling in unweighted and undirected planar graphs. It is known that, in such a graph on $n$ nodes, some labels must consist of $\Omega(n^{1/3})$ bits, but the best known labeling scheme uses labels of length $O(\sqrt{n}\log n)$ [Gavoille, Peleg, P\'erennes, and Raz, J. Algorithms, 2004]. We show that, in fact, labels of length $O(\sqrt{n})$ are enough.

Connected through hyperedge HE-1 (induced by source paper "shorter labels for routing in trees"):
  with members:
    - "near optimal compression for the planar graph metric"
    - "optimal distance labeling schemes for trees"
    - "optimal induced universal graphs and adjacency labeling for trees"
    - "simpler faster and shorter labels for distances in graphs"
    - "sublinear space distance labeling using hubs"
    - "near optimal adjacency labeling scheme for power law graphs"
    - "distance labeling schemes for trees"
    - "a simple and optimal ancestry labeling scheme for trees"

Connected through hyperedge HE-2 (induced by source paper "hardness of exact distance queries in sparse graphs through hub labeling"):
  with members:
    - "near optimal compression for the planar graph metric"
    - "linear size distance preservers"
    - "optimal distance labeling schemes for trees"
    - "simpler faster and shorter labels for distances in graphs"
    - "sublinear space distance labeling using hubs"
    - "maximum matching in turnstile streams"
    - "sublinear distance labeling"
    - "distance labeling schemes for trees"

Connected through hyperedge HE-3 (induced by source paper "distance and routing labeling schemes for cube free median graphs"):
  with members:
    - "on density of subgraphs of cartesian products"
    - "a polynomial time algorithm to compute geodesics in cat 0 cubical complexes"
    - "a counterexample to thiagarajan s conjecture on regular event structures"
    - "simpler faster and shorter labels for distances in graphs"
    - "sublinear distance labeling"
    - "distance labeling schemes for trees"
    - "shortest path problem in rectangular complexes of global nonpositive curvature"
    - "state complexes for metamorphic robots"

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)