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: "adjacency labeling schemes and induced universal graphs"
  Abstract: We describe a way of assigning labels to the vertices of any undirected graph on up to $n$ vertices, each composed of $n/2+O(1)$ bits, such that given the labels of two vertices, and no other information regarding the graph, it is possible to decide whether or not the vertices are adjacent in the graph. This is optimal, up to an additive constant, and constitutes the first improvement in almost 50 years of an $n/2+O(\log n)$ bound of Moon. As a consequence, we obtain an induced-universal graph for $n$-vertex graphs containing only $O(2^{n/2})$ vertices, which is optimal up to a multiplicative constant, solving an open problem of Vizing from 1968. We obtain similar tight results for directed graphs, tournaments and bipartite graphs.

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 "adjacency labelling for planar graphs and beyond"):
  with members:
    - "planar graphs have bounded queue number"
    - "shorter labeling schemes for planar graphs"
    - "an annotated bibliography on 1 planarity"
    - "near optimal induced universal graphs for bounded degree graphs"
    - "optimal induced universal graphs and adjacency labeling for trees"
    - "simpler faster and shorter labels for distances in graphs"
    - "sublinear distance labeling"
    - "distance labeling schemes for trees"

Connected through hyperedge HE-3 (induced by source paper "universal communication universal graphs and graph labeling"):
  with members:
    - "near log convexity of measured heat in discrete time and consequences"
    - "the power of shared randomness in uncertain communication"
    - "an optimal ancestry labeling scheme with applications to xml trees and universal posets"
    - "on the implicit graph conjecture"
    - "communication with contextual uncertainty"
    - "optimal induced universal graphs and adjacency labeling for trees"
    - "contact representations of graphs in 3d"
    - "sublinear distance labeling"

Connected through hyperedge HE-4 (induced by source paper "optimal distance labeling schemes for trees"):
  with members:
    - "optimal induced universal graphs and adjacency labeling for trees"
    - "simpler faster and shorter labels for distances in graphs"
    - "near optimal adjacency labeling scheme for power law graphs"
    - "near optimal labeling schemes for nearest common ancestors"
    - "fast exact shortest path distance queries on large networks by pruned landmark labeling"
    - "new lower and upper bounds for representing sequences"

Connected through hyperedge HE-5 (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"
    - "a simple and optimal ancestry labeling scheme for trees"
    - "near optimal labeling schemes for nearest common ancestors"
    - "labeling schemes for bounded degree graphs"

Connected through hyperedge HE-6 (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"
    - "a simple and optimal ancestry labeling scheme for trees"
    - "labeling schemes for bounded degree graphs"
    - "succinct representations of permutations and functions"

Connected through hyperedge HE-7 (induced by source paper "distance labeling schemes for trees"):
  with members:
    - "simpler faster and shorter labels for distances in graphs"
    - "prioritized metric structures and embedding"
    - "near optimal labeling schemes for nearest common ancestors"
    - "succinct representations of permutations and functions"
    - "labeling schemes with queries"

Connected through hyperedge HE-8 (induced by source paper "simpler faster and shorter labels for distances in graphs"):
  with members:
    - "optimal induced universal graphs and adjacency labeling for trees"
    - "near optimal labeling schemes for nearest common ancestors"
    - "fast exact shortest path distance queries on large networks by pruned landmark labeling"
    - "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)