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 "very sparse additive spanners and emulators"):
  Abstract: We obtain new upper bounds on the additive distortion for graph emulators and spanners on relatively few edges. We introduce a new subroutine called "strip creation," and we combine this subroutine with several other ideas to obtain the following results: #R##N#\item Every graph has a spanner on $O(n^{1+\epsilon})$ edges with $\tilde{O}(n^{1/2 - \epsilon/2})$ additive distortion, for arbitrary $\epsilon\in [0,1]$. \item Every graph has an emulator on $\tilde{O}(n^{1 + \epsilon})$ edges with $\tilde{O}(n^{1/3 - 2\epsilon/3})$ additive distortion whenever $\epsilon \in [0, \frac{1}{5}]$. \item Every graph has a spanner on $\tilde{O}(n^{1 + \epsilon})$ edges with $\tilde{O}(n^{2/3 - 5\epsilon/3})$ additive distortion whenever $\epsilon \in [0, \frac{1}{4}]$. #R##N#Our first spanner has the new best known asymptotic edge-error tradeoff for additive spanners whenever $\epsilon \in [0, \frac{1}{7}]$. Our second spanner has the new best tradeoff whenever $\epsilon \in [\frac{1}{7}, \frac{3}{17}]$. Our emulator has the new best asymptotic edge-error tradeoff whenever $\epsilon \in [0, \frac{1}{5}]$.

Includes members:
  Member "additive spanners a simple construction":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "weighted additive spanners")
  Member "on pairwise spanners":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "weighted additive spanners")

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)