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 "approximate distance oracles subject to multiple vertex failures"):
  Abstract: Given an undirected graph $G=(V,E)$ of $n$ vertices and $m$ edges with weights in $[1,W]$, we construct vertex sensitive distance oracles (VSDO), which are data structures that preprocess the graph, and answer the following kind of queries: Given a source vertex $u$, a target vertex $v$, and a batch of $d$ failed vertices $D$, output (an approximation of) the distance between $u$ and $v$ in $G-D$ (that is, the graph $G$ with vertices in $D$ removed). An oracle has stretch $\alpha$ if it always holds that $\delta_{G-D}(u,v)\le\tilde{\delta}(u,v)\le\alpha\cdot\delta_{G-D}(u,v)$, where $\delta_{G-D}(u,v)$ is the actual distance between $u$ and $v$ in $G-D$, and $\tilde{\delta}(u,v)$ is the distance reported by the oracle. #R##N#In this paper we construct efficient VSDOs for any number $d$ of failures. For any constant $c\geq 1$, we propose two oracles: #R##N#* The first oracle has size $n^{2+1/c}(\log n/\epsilon)^{O(d)}\cdot \log W$, answers a query in ${\rm poly}(\log n,d^c,\log\log W,\epsilon^{-1})$ time, and has stretch $1+\epsilon$, for any constant $\epsilon>0$. #R##N#* The second oracle has size $n^{2+1/c}{\rm poly}(\log (nW),d)$, answers a query in ${\rm poly}(\log n,d^c,\log\log W)$ time, and has stretch ${\rm poly}(\log n,d)$. #R##N#Both of these oracles can be preprocessed in time polynomial in their space complexity. These results are the first approximate distance oracles of poly-logarithmic query time for any constant number of vertex failures in general undirected graphs. Previously there are $(1+\epsilon)$-approximate $d$-edge sensitive distance oracles [Chechik et al. 2017] answering distance queries when $d$ edges fail, which have size $O(n^2(\log n/\epsilon)^d\cdot d\log W)$ and query time ${\rm poly}(\log n, d, \log\log W)$.

Includes members:
  Member "sensitive distance and reachability oracles for large batch updates":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "dynamic approximate shortest paths and beyond subquadratic and worst case update time")
  Member "generic single edge fault tolerant exact distance oracle":
    also connected through other hyperedges:
      (none)
  Member "a trivial yet optimal solution to vertex fault tolerant spanners":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "efficient and simple algorithms for fault tolerant spanners")
  Member "exact distance oracles for planar graphs with failing vertices":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "planar diameter via metric compression")
  Member "preserving distances in very faulty graphs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a brief note on single source fault tolerant reachability")
  Member "optimal vertex fault tolerant spanners for fixed stretch":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "efficient and simple algorithms for fault tolerant spanners")
  Member "connectivity oracles for graphs subject to vertex failures":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "sensitive distance and reachability oracles for large batch updates")
  Member "multiple edge fault tolerant approximate shortest path trees":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "generic single edge fault tolerant exact distance oracle")

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)