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 induced universal graphs and adjacency labeling for trees"):
  Abstract: We show that there exists a graph $G$ with $O(n)$ nodes, where any forest of $n$ nodes is a node-induced subgraph of $G$. Furthermore, for constant arboricity $k$, the result implies the existence of a graph with $O(n^k)$ nodes that contains all $n$-node graphs as node-induced subgraphs, matching a $\Omega(n^k)$ lower bound. The lower bound and previously best upper bounds were presented in Alstrup and Rauhe (FOCS'02). Our upper bounds are obtained through a $\log_2 n +O(1)$ labeling scheme for adjacency queries in forests. #R##N#We hereby solve an open problem being raised repeatedly over decades, e.g. in Kannan, Naor, Rudich (STOC 1988), Chung (J. of Graph Theory 1990), Fraigniaud and Korman (SODA 2010).

Includes members:
  Member "an optimal ancestry labeling scheme with applications to xml trees and universal posets":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "universal communication universal graphs and graph labeling")
  Member "popular conjectures as a barrier for dynamic planar graph algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "rounding dynamic matchings against an adaptive adversary")
  Member "near optimal induced universal graphs for bounded degree graphs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (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-4 (induced by source paper "shorter labels for routing in trees")
  Member "sublinear distance labeling":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "adjacency labelling for planar graphs and beyond")
  Member "a simple and optimal ancestry labeling scheme for trees":
    also connected through other hyperedges:
      - Hyperedge HE-6 (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-7 (induced by source paper "shorter labels for routing in trees")
  Member "labeling schemes for bounded degree graphs":
    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)