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 "eccentricity terrain of delta hyperbolic graphs"):
  Abstract: A graph $G=(V,E)$ is $\delta$-hyperbolic if for any four vertices $u,v,w,x$, the two larger of the three distance sums $d(u,v)+d(w,x)$, $d(u,w)+d(v,x)$, and $d(u,x)+d(v,w)$ differ by at most $2\delta \geq 0$. Recent work shows that many real-world graphs have small hyperbolicity $\delta$. This paper describes the eccentricity terrain of a $\delta$-hyperbolic graph. The eccentricity function $e_G(v)=\max\{d(v,u) : u \in V\}$ partitions the vertex set of $G$ into eccentricity layers $C_{k}(G) = \{v \in V : e(v)=rad(G)+k\}$, $k \in \mathbb{N}$, where $rad(G)=\min\{e_G(v): v\in V\}$ is the radius of $G$. The paper studies the eccentricity layers of vertices along shortest paths, identifying such terrain features as hills, plains, valleys, terraces, and plateaus. It introduces the notion of $\beta$-pseudoconvexity, which implies Gromov's $\epsilon$-quasiconvexity, and illustrates the abundance of pseudoconvex sets in $\delta$-hyperbolic graphs. In particular, it shows that all sets $C_{\leq k}(G)=\{v\in V : e_G(v) \leq rad(G) + k\}$, $k\in \mathbb{N}$, are $(2\delta-1)$-pseudoconvex. Additionally, several bounds on the eccentricity of a vertex are obtained which yield a few approaches to efficiently approximating all eccentricities. An $O(\delta |E|)$ time eccentricity approximation $\hat{e}(v)$, for all $v\in V$, is presented that uses distances to two mutually distant vertices and satisfies $e_G(v)-2\delta \leq \hat{e}(v) \leq {e_G}(v)$. It also shows existence of two eccentricity approximating spanning trees $T$, one constructible in $O(\delta |E|)$ time and the other in $O(|E|)$ time, which satisfy ${e}_G(v) \leq e_T(v) \leq {e}_G(v)+4\delta+1$ and ${e}_G(v) \leq e_T(v) \leq {e}_G(v)+6\delta$, respectively. Thus, the eccentricity terrain of a tree gives a good approximation (up-to an additive error $O(\delta))$ of the eccentricity terrain of a $\delta$-hyperbolic graph.

Includes members:
  Member "fast approximation and exact computation of negative curvature parameters of graphs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "why did the shape of your network change on detecting network anomalies via non local curvatures")
  Member "revisiting radius diameter and all eccentricity computation in graphs through certificates":
    also connected through other hyperedges:
      (none)
  Member "core congestion is inherent in hyperbolic networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "fast approximation and exact computation of negative curvature parameters of graphs")
  Member "metric tree like structures in real life networks an empirical study":
    also connected through other hyperedges:
      (none)
  Member "computing the gromov hyperbolicity of a discrete metric space":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "computationally tractable riemannian manifolds for graph embeddings")

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.DM(Discrete Mathematics)