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 "graph coloring via degeneracy in streaming and other space conscious models"):
  Abstract: We study the problem of coloring a given graph using a small number of colors in several well-established models of computation for big data. These include the data streaming model, the general graph query model, the massively parallel computation (MPC) model, and the CONGESTED-CLIQUE and the LOCAL models of distributed computation. On the one hand, we give algorithms with sublinear complexity, for the appropriate notion of complexity in each of these models. Our algorithms color a graph $G$ using about $\kappa(G)$ colors, where $\kappa(G)$ is the degeneracy of $G$: this parameter is closely related to the arboricity $\alpha(G)$. As a function of $\kappa(G)$ alone, our results are close to best possible, since the optimal number of colors is $\kappa(G)+1$. #R##N#On the other hand, we establish certain lower bounds indicating that sublinear algorithms probably cannot go much further. In particular, we prove that any randomized coloring algorithm that uses $\kappa(G)+1$ many colors, would require $\Omega(n^2)$ storage in the one pass streaming model, and $\Omega(n^2)$ many queries in the general graph query model, where $n$ is the number of vertices in the graph. These lower bounds hold even when the value of $\kappa(G)$ is known in advance; at the same time, our upper bounds do not require $\kappa(G)$ to be given in advance.

Includes members:
  Member "simple graph coloring algorithms for congested clique and massively parallel computation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "log diameter rounds algorithms for 2 vertex and 2 edge connectivity")
  Member "greedy and local ratio algorithms in the mapreduce model":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "equivalence classes and conditional hardness in massively parallel computations")
  Member "dynamic algorithms for graph coloring":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "coarse grained complexity for dynamic algorithms")
  Member "dynamic graph coloring":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "trade offs in dynamic coloring for bipartite and general graphs")
  Member "simple and near optimal distributed coloring for sparse graphs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "property testing of planarity in the congest model")
  Member "densest subgraph in dynamic graph streams":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "near optimal fully dynamic densest subgraph")
  Member "local conflict coloring":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "distributed edge coloring in time quasi polylogarithmic in delta")
  Member "hypergraph two coloring in the streaming model":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "coloring in graph streams")

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)