human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "near additive spanners and near exact hopsets a unified view"
  Abstract: Given an {\em unweighted} undirected graph $G = (V,E)$, and a pair of parameters $\epsilon > 0$, $\beta = 1,2,\ldots$, a subgraph $G' =(V,H)$, $H \subseteq E$, of $G$ is a {\em $(1+\epsilon,\beta)$-spanner} (aka, a {\em near-additive spanner}) of $G$ if for every $u,v \in V$, $$d_{G'}(u,v) \le (1+\epsilon)d_G(u,v) + \beta~.$$ It was shown in \cite{EP01} that for any $n$-vertex $G$ as above, and any $\epsilon > 0$ and $\kappa = 1,2,\ldots$, there exists a $(1+\epsilon,\beta)$-spanner $G'$ with $O_{\epsilon,\kappa}(n^{1+1/\kappa})$ edges, with $$\beta = \beta_{EP} = \left({{\log \kappa} \over \epsilon}\right)^{\log \kappa - 2}~.$$ This bound remains state-of-the-art, and its dependence on $\epsilon$ (for the case of small $\kappa$) was shown to be tight in \cite{ABP18}. #R##N#Given a {\em weighted} undirected graph $G = (V,E,\omega)$, and a pair of parameters $\epsilon > 0$, $\beta = 1,2,\ldots$, a graph $G'= (V,H,\omega')$ is a {\em $(1+\epsilon,\beta)$-hopset} (aka, a {\em near-exact hopset}) of $G$ if for every $u,v \in V$, $$d_G(u,v) \le d_{G\cup G'}^{(\beta)}(u,v) \le (1+\epsilon)d_G(u,v)~,$$ where $ d_{G\cup G'}^{(\beta)}(u,v)$ stands for a $\beta$-(hop)-bounded distance between $u$ and $v$ in the union graph $G \cup G'$. It was shown in \cite{EN16} that for any $n$-vertex $G$ and $\epsilon$ and $\kappa$ as above, there exists a $(1+\epsilon,\beta)$-hopset with $\tilde{O}(n^{1+1/\kappa})$ edges, with $\beta = \beta_{EP}$. #R##N#Not only the two results of \cite{EP01} and \cite{EN16} are strikingly similar, but so are also their proof techniques. Moreover, Thorup-Zwick's later construction of near-additive spanners \cite{TZ06} was also shown in \cite{EN19,HP17} to provide hopsets with analogous (to that of \cite{TZ06}) properties. #R##N#In this survey we explore this intriguing phenomenon, sketch the basic proof techniques used for these results, and highlight open questions.

Connected through hyperedge HE-1 (induced by source paper "exponentially faster shortest paths in the congested clique"):
  with members:
    - "near additive spanners in low polynomial deterministic congest time"
    - "fast approximate shortest paths in the congested clique"
    - "congested clique algorithms for graph spanners"
    - "sparse matrix multiplication and triangle listing in the congested clique model"
    - "linear size hopsets with small hopbound and distributed routing with low memory"
    - "thorup zwick emulators are universally optimal hopsets"
    - "towards a complexity theory for the congested clique"
    - "further algebraic algorithms in the congested clique model and applications to graph theoretic problems"

Connected through hyperedge HE-2 (induced by source paper "graph spanners a tutorial review"):
  with members:
    - "some general structure for extremal sparsification problems"
    - "weighted additive spanners"
    - "near additive spanners in low polynomial deterministic congest time"
    - "multi level graph sketches via single level solvers"
    - "almost shortest paths and pram distance oracles in weighted graphs"
    - "an fpt algorithm for minimum additive spanner problem"
    - "distributed construction of light networks"
    - "lasserre integrality gaps for graph spanners and related problems"

Question: Please tell me which class the center node 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)