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: "optimal distance labeling schemes for trees"
  Abstract: We resolve the complexity of distance labeling schemes for trees. #R##N#For arbitrary distances, we show how to assign labels of $1/4\log^2n+o(\log^2n)$ bits to every node so that we can determine the distance between any two nodes given only their two labels. This closes the line of research initiated by Gavoille et al. [SODA '01] who gave an $O(\log^2n)$ bits upper bound and a $1/8\log^2n-O(\log n)$ bits lower bound, and followed by Alstrup et al. [ICALP '16] who gave a $1/2 \log^2 n + O(\log n)$ bits upper bound and a $1/4\log^2n-O(\log n)$ bits lower bound. #R##N#Next, for distances bounded by $k$, we show how to construct labels whose length is the minimum between $\log n+O(k\log(\log n/k))$ and $O(\log n \cdot \log(k/\log n))$. The query time in both cases is constant. We complement our upper bounds with almost tight lower bounds of $\log n+\Omega(k\log(\log n / (k\log k)))$ and $\Omega(\log n \cdot \log(k/\log n))$. This line of research was initiated by Kaplan and Milo [WADS '01] who constructed labels of length $\log n+O(k\sqrt{\log n})$, and followed by the $\log n+O(k^2(\log(k\log n))$ labeling scheme of Alstrup, Bille, and Rauhe [SODA '03] whose query-time is $O(k^2)$ and the $\log n+O(k\log(k\log(n/k)))$ labeling scheme of Gavoille and Labourel [PODC '07] whose query-time is $O(k)$. #R##N#Finally, we consider $(1+\epsilon)$-approximate distances. We prove an $O(\log(1/\epsilon)\cdot \log n)$ upper bound and a matching $\Omega(\log(1/\epsilon)\cdot \log n)$ lower bound. This improves the recent $O(1/\epsilon \cdot \log n)$ upper bound of Alstrup et al. [ICALP '16].

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"
    - "a note on distance labeling in planar graphs"
    - "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"
    - "a note on distance labeling in planar graphs"
    - "linear size distance preservers"
    - "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 "shorter labeling schemes for planar graphs"):
  with members:
    - "planar graphs as l intersection or l contact graphs"
    - "proximity results and faster algorithms for integer programming using the steinitz lemma"
    - "optimal induced universal graphs and adjacency labeling for trees"
    - "simpler faster and shorter labels for distances in graphs"
    - "sublinear space distance labeling using hubs"
    - "new routing techniques and their applications"
    - "near optimal labeling schemes for nearest common ancestors"

Connected through hyperedge HE-4 (induced by source paper "the complexity of mean payoff games using universal graphs"):
  with members:
    - "parity games and universal 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.DS(Data Structures and Algorithms)