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 "fast deterministic constructions of linear size spanners and skeletons"):
  Abstract: In the distributed setting, the only existing constructions of \textit{sparse skeletons}, (i.e., subgraphs with $O(n)$ edges) either use randomization or large messages, or require $\Omega(D)$ time, where $D$ is the hop-diameter of the input graph $G$. We devise the first deterministic distributed algorithm in the CONGEST model (i.e., uses small messages) for constructing linear-size skeletons in time $2^{O(\sqrt{{\log n}\cdot{\log{\log n}}})}$. We can also compute a linear-size spanner with stretch $polylog(n)$ in low deterministic polynomial time, i.e., $O(n^\rho)$ for an arbitrarily small constant $\rho >0$, in the CONGEST model. Yet another algorithm that we devise runs in $O({\log n})^{\kappa-1}$ time, for a parameter $\kappa=1,2,\dots,$ and constructs an $O({\log n})^{\kappa-1}$ spanner with $O(n^{1+1/\kappa})$ edges. All our distributed algorithms are lightweight from the computational perspective, i.e., none of them employs any heavy computations.

Includes members:
  Member "deterministic distributed ruling sets of line graphs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "near additive spanners in low polynomial deterministic congest time")
  Member "improved deterministic distributed construction of spanners":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "near additive spanners in low polynomial deterministic congest time")
  Member "efficient algorithms for constructing very sparse spanners and emulators":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "exponentially faster shortest paths in the congested clique")
  Member "a fast network decomposition algorithm and its applications to constant time distributed computation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "message reduction in the local model is a free lunch")
  Member "parallel graph decompositions using random shifts":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "scattering and sparse partitions and their applications")

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.DC(Distributed, Parallel, and Cluster Computing)