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 "trade offs in dynamic coloring for bipartite and general graphs"):
  Abstract: We present trade-offs in the incremental and fully dynamic settings to maintian a proper coloring. For any fully dynamic $2$-coloring algorithm, the maximum of the update time, number of recolorings, and query time is $\Omega(\log n)$. We present a deterministic fully dynamic $2$-coloring algorithm with $O(\log^2 n)$ amortized update time, $O(\log n)$ amortized query time, and one recoloring in the worst case. For any incremental $2$-coloring algorithm which explicitly maintains the color of every vertex after each update, the amortized update time and the amortized number of recolorings is $\Omega(\log n)$. For such an algorithm, in the worst case the update time and the number of recolorings is $\Omega(n)$. We then design a deterministic incremental $2$-coloring algorithm which explicitly maintains the color of every vertex after each update, with amortized $O(\log n)$ update time and amortized $O(\log n)$ many recolorings. Further, in the worst case the update time and the number of recolorings is $O(n)$. Further, we present a deterministic incremental $(1+2 \log n)$-coloring algorithm which explicitly maintains the color of every vertex after each update, with $O(\alpha(n))$ amortized update time, at most one recoloring and $O(1)$ query time. We then show a deterministic incremental $2$-coloring algorithm which does not maintain color of every vertex after each update, with amortized $O(\alpha(n))$ update time, amortized $O(\alpha(n))$ recolorings, and amortized $O(\alpha(n))$ query time.  For general graphs and graphs of bounded arboricity $\gamma$ and maximum degree $\Delta$ we present a deterministic $(\Delta+1)$-coloring algorithm with $O(\sqrt{m})$ update time, $O(1)$ query time, and one recoloring. Finally, we show a deterministic $(\Delta+1)$-coloring algorithm with amortized $O(\gamma + \log{n})$ update time, $O(1)$ query time, and one recoloring.

Includes members:
  Member "constant time dynamic delta 1 coloring and weight approximation for minimum spanning forest dynamic algorithms meet property testing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "dynamic data structures for interval coloring")
  Member "improved dynamic graph coloring":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "dynamic data structures for interval coloring")
  Member "dynamic coloring for bipartite and general graphs":
    also connected through other hyperedges:
      (none)
  Member "fully dynamic maximal independent set with sublinear update time":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "coarse grained complexity for dynamic algorithms")
  Member "dynamic algorithms for graph coloring":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "coarse grained complexity for dynamic algorithms")
  Member "dynamic graph coloring":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "improved dynamic graph coloring")
  Member "fully dynamic maximal matching in constant update time":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "dynamic graph algorithms with batch updates in the massively parallel computation model")
  Member "simple deterministic algorithms for fully dynamic maximal matching":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "dynamic graph algorithms with batch updates in the massively parallel computation model")

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)