human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "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].

Includes members:
  Member "optimal induced universal graphs and adjacency labeling for trees":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "shorter labels for routing in trees")
  Member "simpler faster and shorter labels for distances in graphs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "shorter labels for routing in trees")
  Member "near optimal adjacency labeling scheme for power law graphs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "shorter labels for routing in trees")
  Member "adjacency labeling schemes and induced universal graphs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "shorter labels for routing in trees")
  Member "near optimal labeling schemes for nearest common ancestors":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "shorter labels for routing in trees")
  Member "fast exact shortest path distance queries on large networks by pruned landmark labeling":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "relaxing relationship queries on graph data")
  Member "new lower and upper bounds for representing sequences":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "run compressed rank select for large alphabets")

Question: Please tell me which class the source paper 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)