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 simple and optimal ancestry labeling scheme for trees"
  Abstract: We present a $\lg n + 2 \lg \lg n+3$ ancestry labeling scheme for trees. The problem was first presented by Kannan et al. [STOC 88'] along with a simple $2 \lg n$ solution. Motivated by applications to XML files, the label size was improved incrementally over the course of more than 20 years by a series of papers. The last, due to Fraigniaud and Korman [STOC 10'], presented an asymptotically optimal $\lg n + 4 \lg \lg n+O(1)$ labeling scheme using non-trivial tree-decomposition techniques. By providing a framework generalizing interval based labeling schemes, we obtain a simple, yet asymptotically optimal solution to the problem. Furthermore, our labeling scheme is attained by a small modification of the original $2 \lg n$ solution.

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 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"

Connected through hyperedge HE-2 (induced by source paper "an optimal ancestry labeling scheme with applications to xml trees and universal posets"):
  with members:
    - "optimal induced universal graphs and adjacency labeling for trees"
    - "improved ancestry labeling scheme for trees"
    - "adjacency labeling schemes and induced universal graphs"
    - "near optimal labeling schemes for nearest common ancestors"
    - "labeling schemes for bounded degree graphs"

Connected through hyperedge HE-3 (induced by source paper "optimal induced universal graphs and adjacency labeling for trees"):
  with members:
    - "an optimal ancestry labeling scheme with applications to xml trees and universal posets"
    - "popular conjectures as a barrier for dynamic planar graph algorithms"
    - "near optimal induced universal graphs for bounded degree graphs"
    - "simpler faster and shorter labels for distances in graphs"
    - "sublinear distance labeling"
    - "adjacency labeling schemes and induced universal graphs"
    - "labeling schemes for bounded degree graphs"
    - "succinct representations of permutations and 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)