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 "shortest path centrality and the all pairs shortest paths problem via vc dimension theory"):
  Abstract: In this paper we are interested in a version of the All-pairs Shortest Paths problem (APSP) that fits neither in the exact nor in the approximate case. We define a measure of centrality of a shortest path, related to the "importance" of such shortest path in the graph, and propose a randomized algorithm that, for {\it any fixed constants} $0 < \epsilon$, $ \delta < 1$, given an undirected graph $G$ with non-negative edge weights, outputs with probability $1 - \delta$ a $n^2$ sized matrix in time $\mathcal{O}(n^2 \lg n)$ containing the (exact) shortest path between every pair of vertices $(u,v)$ that has centrality at least $\epsilon$. The central idea is to sample shortest path trees so that all shortest paths with the desired centrality are covered and our main contribution is showing a bound on the sample size using tools from VC-dimension theory. This bound is tighter than the bound given by standard Hoeffding and union bounds, since VC-dimension theory captures the combinatorial structure of the input graph.

Includes members:
  Member "estimating the percolation centrality of large networks through pseudo dimension theory":
    also connected through other hyperedges:
      (none)
  Member "almost shortest paths and pram distance oracles in weighted graphs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "weighted additive spanners")
  Member "approximating apsp without scaling equivalence of approximate min plus and exact min max":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "approximating subset sum is equivalent to min plus convolution")
  Member "abra approximating betweenness centrality in static and dynamic graphs with rademacher averages":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "simple and fast distributed computation of betweenness centrality")
  Member "on the shoshan zwick algorithm for the all pairs shortest path problem":
    also connected through other hyperedges:
      (none)
  Member "popular conjectures imply strong lower bounds for dynamic problems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "new algorithms and hardness for incremental single source shortest paths in directed graphs")
  Member "faster all pairs shortest paths via circuit complexity":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "deterministic algorithms for decremental approximate shortest paths faster and simpler")
  Member "shape fitting on point sets with probability distributions":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "abra approximating betweenness centrality in static and dynamic graphs with rademacher averages")

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)