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 "shorter labels for routing in trees"):
  Abstract: A routing labeling scheme assigns a binary string, called a label, to each node in a network, and chooses a distinct port number from $\{1,\ldots,d\}$ for every edge outgoing from a node of degree $d$. Then, given the labels of $u$ and $w$ and no other information about the network, it should be possible to determine the port number corresponding to the first edge on the shortest path from $u$ to $w$. In their seminal paper, Thorup and Zwick [SPAA 2001] designed several routing methods for general weighted networks. An important technical ingredient in their paper that according to the authors ``may be of independent practical and theoretical interest'' is a routing labeling scheme for trees of arbitrary degrees. For a tree on $n$ nodes, their scheme constructs labels consisting of $(1+o(1))\log n$ bits such that the sought port number can be computed in constant time. Looking closer at their construction, the labels consist of $\log n + O(\log n\cdot \log\log\log n / \log\log n)$ bits. Given that the only known lower bound is $\log n+\Omega(\log\log n)$, a natural question that has been asked for other labeling problems in trees is to determine the asymptotics of the smaller-order term. #R##N#We make the first (and significant) progress in 19 years on determining the correct second-order term for the length of a label in a routing labeling scheme for trees on $n$ nodes. We design such a scheme with labels of length $\log n+O((\log\log n)^{2})$. Furthermore, we modify the scheme to allow for computing the port number in constant time at the expense of slightly increasing the length to $\log n+O((\log\log n)^{3})$.

Includes members:
  Member "near optimal compression for the planar graph metric":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "planar diameter via metric compression")
  Member "a note on distance labeling in planar graphs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "hardness of exact distance queries in sparse graphs through hub labeling")
  Member "optimal distance labeling schemes for trees":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "hardness of exact distance queries in sparse graphs through hub labeling")
  Member "optimal induced universal graphs and adjacency labeling for trees":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "adjacency labelling for planar graphs and beyond")
  Member "simpler faster and shorter labels for distances in graphs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "adjacency labelling for planar graphs and beyond")
  Member "sublinear space distance labeling using hubs":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "hardness of exact distance queries in sparse graphs through hub labeling")
  Member "near optimal adjacency labeling scheme for power law graphs":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "optimal distance labeling schemes for trees")
  Member "distance labeling schemes for trees":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "adjacency labelling for planar graphs and beyond")

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)