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 "massively parallel approximate distance sketches"):
  Abstract: Data structures that allow efficient distance estimation (distance oracles, distance sketches, etc.) have been extensively studied, and are particularly well studied in centralized models and classical distributed models such as CONGEST. We initiate their study in newer (and arguably more realistic) models of distributed computation such as the Congested Clique model and the Massively Parallel Computation (MPC) model, as well as in related big data models such as streaming and semi-streaming. We provide algorithms for constructing the well-known Thorup-Zwick distance oracle (or distance sketches) in these different computational models and discuss the tradeoffs between various complexity measures such as space, time, stretch, and message complexity. #R##N#One key component we use to construct distance sketches are the hopsets of Elkin and Neiman 2016. In particular, we show that these hopsets can be constructed efficiently in the MPC model, even in the very low memory setting. This result has additional applications such as the first subpolynomial algorithm for approximate single-source shortest paths for weighted graphs in the low memory MPC setting.

Includes members:
  Member "fast approximate shortest paths in the congested clique":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "exponentially faster shortest paths in the congested clique")
  Member "mapreduce meets fine grained complexity mapreduce algorithms for apsp matrix multiplication 3 sum and beyond":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "massively parallel algorithms for distance approximation and spanners")
  Member "near optimal approximate shortest paths and transshipment in distributed and streaming models":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "polynomial pass lower bounds for graph streaming algorithms")
  Member "hopsets with constant hopbound and applications to approximate shortest paths":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "new algorithms and hardness for incremental single source shortest paths in directed graphs")
  Member "on efficient distributed construction of near optimal routing schemes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "new alpha beta spanners and hopsets")
  Member "parallel metric tree embedding based on an algebraic view on moore bellman ford":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "massively parallel algorithms for distance approximation and spanners")
  Member "a deterministic almost tight distributed algorithm for approximating single source shortest paths":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "two player hidden pointer chasing and multi pass lower bounds in turnstile streams")
  Member "distributed computation of large scale graph problems":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "equivalence classes and conditional hardness in massively parallel computations")

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)