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 "planar diameter via metric compression"):
  Abstract: We develop a new approach for distributed distance computation in planar graphs that is based on a variant of the metric compression problem recently introduced by Abboud et al. [SODA'18]. One of our key technical contributions is in providing a compression scheme that encodes all $S \times T$ distances using $\widetilde{O}(|S|\cdot poly(D)+|T|)$ bits for unweighted graphs with diameter $D$. This significantly improves the state of the art of $\widetilde{O}(|S|\cdot 2^{D}+|T| \cdot D)$ bits. We also consider an approximate version of the problem for \emph{weighted} graphs, where the goal is to encode $(1+\epsilon)$ approximation of the $S \times T$ distances. At the heart of this compact compression scheme lies a VC-dimension type argument on planar graphs. This efficient compression scheme leads to several improvements and simplifications in the setting of diameter computation, most notably in the distributed setting: #R##N#- There is an $\widetilde{O}(D^5)$-round randomized distributed algorithm for computing the diameter in planar graphs, w.h.p. #R##N#- There is an $\widetilde{O}(D^3)+ poly(\log n/\epsilon)\cdot D^2$-round randomized distributed algorithm for computing an $(1+\epsilon)$ approximation of the diameter in weighted graphs with polynomially bounded weights, w.h.p. #R##N#No sublinear round algorithms were known for these problems before. These distributed constructions are based on a new recursive graph decomposition that preserves the (unweighted) diameter of each of the subgraphs up to a logarithmic term. Using this decomposition, we also get an \emph{exact} SSSP tree computation within $\widetilde{O}(D^2)$ rounds.

Includes members:
  Member "exact distance oracles for planar graphs with failing vertices":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "approximate distance oracles subject to multiple vertex failures")
  Member "minor excluded network families admit fast distributed algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "near optimal schedules for simultaneous multicasts")
  Member "distributed treewidth computation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "low congestion shortcut and graph parameters")
  Member "faster distributed shortest path approximations via shortcuts":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "dynamic low stretch trees via dynamic low diameter decompositions")
  Member "constant query time 1 epsilon approximate distance oracle for planar graphs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "almost optimal distance oracles for planar graphs")
  Member "fast and compact exact distance oracle for planar graphs":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "almost optimal distance oracles for planar graphs")
  Member "voronoi diagrams on planar graphs and computing the diameter in deterministic tilde o n 5 3 time":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "diameter computation on h minor free graphs and graphs of bounded distance vc dimension")
  Member "better tradeoffs for exact distance oracles in planar graphs":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a divide and conquer algorithm for two point l_1 shortest path queries in polygonal domains")

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)