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 "deterministic distributed delta o delta edge coloring and vertex coloring of graphs with bounded diversity"):
  Abstract: We consider coloring problems in the distributed message-passing setting. The previously-known deterministic algorithms for edge-coloring employed at least (2Delta - 1) colors, even though any graph admits an edge-coloring with Delta + 1 colors [V64]. Moreover, the previously-known deterministic algorithms that employed at most O(Delta) colors required superlogarithmic time [B15,BE10,BE11,FHK15]. In the current paper we devise deterministic edge-coloring algorithms that employ only Delta + o(Delta) colors, for a very wide family of graphs. Specifically, as long as the arboricity is a = O(Delta^{1 - \epsilon}), for a constant epsilon > 0, our algorithm computes such a coloring within {polylogarithmic} deterministic time. We also devise significantly improved deterministic edge-coloring algorithms for {general graphs} for a very wide range of parameters. Specifically, for any value $\chi$ in the range [4Delta, 2^{o(log Delta)} \cdot Delta], our \chi-edge-coloring algorithm has smaller running time than the best previously-known \chi-edge-coloring algorithms. Our algorithms are actually much more general, since edge-coloring is equivalent to {vertex-coloring of line graphs.} Our method is applicable to vertex-coloring of the family of graphs with {bounded diversity} that contains line graphs, line graphs of hypergraphs, and many other graphs. #R##N#Our results are obtained using a novel technique that connects vertices or edges in a certain way that reduces clique size. The resulting structures, which we call {connectors}, can be colored more efficiently than the original graph. Moreover, the color classes constitute simpler subgraphs that can be colored even more efficiently using appropriate connectors. Hence, we recurse until we obtain sufficiently simple structures that are colored directly. We introduce several types of connectors that are useful for various scenarios.

Includes members:
  Member "distributed degree splitting edge coloring and orientations":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "distributed edge coloring in time quasi polylogarithmic in delta")
  Member "local conflict coloring":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "distributed edge coloring in time quasi polylogarithmic in delta")
  Member "toward more localized local algorithms removing assumptions concerning global knowledge":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "faster deterministic distributed coloring through recursive list coloring")
  Member "the locality of distributed symmetry breaking":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "distributed maximum matching verification in congest")
  Member "deterministic distributed vertex coloring in polylogarithmic time":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "smaller cuts higher lower bounds")
  Member "distributed deterministic edge coloring using bounded neighborhood independence":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "faster deterministic distributed coloring through recursive list coloring")

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)