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 "fully dynamic k center clustering in doubling metrics"):
  Abstract: In the $k$-center clustering problem, we are given a set of $n$ points in a metric space and a parameter $k \leq n$. The goal is to select $k$ designated points, referred to as \emph{centers}, such that the maximum distance of any point to its closest center is minimized. This notion of clustering is of fundamental importance and has been extensively studied. #R##N#We study a \emph{dynamic} variant of the $k$-center clustering problem, where the goal is to maintain a clustering with small approximation ratio while supporting an intermixed update sequence of insertions and deletions of points with small update time. Moreover, the data structure should be able to support the following queries for any given point: (1) report whether this point is a center or (2) determine the cluster this point is assigned to. #R##N#We present a deterministic dynamic algorithms for the $k$-center clustering problem that achieves a $(2+\epsilon)$-approximation with $O(2^{O(\kappa)} \log\Delta \log\log\Delta \cdot \epsilon^{-1} \ln \epsilon^{-1})$ update time and $O(\log \Delta)$ query time, where $\kappa$ bounds the doubling dimension of the metric and $\Delta$ is the aspect ratio. Our running and query times are independent of the number of centers $k$, and are poly-logarithmic when the metric has constant doubling dimension and the aspect ratio is bounded by a polynomial.

Includes members:
  Member "dynamic low stretch trees via dynamic low diameter decompositions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "practice of streaming and dynamic graphs concepts models systems and parallelism")
  Member "a tree structure for dynamic facility location":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the power of recourse better algorithms for facility location in online and dynamic models")
  Member "fully dynamic hierarchical diameter k clustering and k center":
    also connected through other hyperedges:
      (none)
  Member "small space stream summary for matroid center":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "coreset based strategies for robust center type problems")
  Member "expander decomposition and pruning faster stronger and simpler":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "coarse grained complexity for dynamic algorithms")
  Member "dynamic clustering to minimize the sum of radii":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a tree structure for dynamic facility location")
  Member "the new data and new challenges in multimedia research":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "large scale weakly supervised pre training for video action recognition")
  Member "fast construction of nets in low dimensional metrics and their applications":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a data dependent algorithm for querying earth mover s distance with low doubling dimension")

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)