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: "the mst of symmetric disk graphs in arbitrary metrics is light"
  Abstract: Consider an n-point metric M = (V,delta), and a transmission range assignment r: V \rightarrow \mathbb R^+ that maps each point v in V to the disk of radius r(v) around it. The {symmetric disk graph} (henceforth, SDG) that corresponds to M and r is the undirected graph over V whose edge set includes an edge (u,v) if both r(u) and r(v) are no smaller than delta(u,v). SDGs are often used to model wireless communication networks. #R##N#Abu-Affash, Aschner, Carmi and Katz (SWAT 2010, \cite{AACK10}) showed that for any {2-dimensional Euclidean} n-point metric M, the weight of the MST of every {connected} SDG for M is O(log n) w(MST(M)), and that this bound is tight. However, the upper bound proof of \cite{AACK10} relies heavily on basic geometric properties of 2-dimensional Euclidean metrics, and does not extend to higher dimensions. A natural question that arises is whether this surprising upper bound of \cite{AACK10} can be generalized for wider families of metrics, such as 3-dimensional Euclidean metrics. #R##N#In this paper we generalize the upper bound of Abu-Affash et al. \cite{AACK10} for Euclidean metrics of any dimension. Furthermore, our upper bound extends to {arbitrary metrics} and, in particular, it applies to any of the normed spaces ell_p. Specifically, we demonstrate that for {any} n-point metric M, the weight of the MST of every connected SDG for M is O(log n) w(MST(M)).

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.CG(Computational Geometry)