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: "approximating the diameter of a graph"
  Abstract: In this paper we consider the fundamental problem of approximating the diameter D of directed or undirected graphs. In a seminal paper, Aingworth, Chekuri, Indyk and Motwani [SIAM J. Comput. 1999] presented an algorithm that computes in e O(m √ n + n 2 ) time an estimate ˆ D for the diameter of an n-node, m-edge graph, such that ⌊2/3D⌋ ≤ ˆ D ≤ D. In this paper we present an algorithm that produces the same estimate in e O(m √ n) expected running time. We then provide strong evidence that a better approximation may be hard to obtain if we insist on an O(m 2 " ) running time. In particular, we show that if there is some constant " > 0 so that there is an algorithm for undirected unweighted graphs that runs in O(m 2 " ) time and produces an approximation ˆ D such that (2/3 + ")D ≤ ˆ D ≤ D, then SAT for CNF formulas onn variables can be solved in O � ((2 − �) n ) time for some constant � > 0, and the strong exponential time hypothesis of [Impagliazzo, Paturi, Zane JCSS’01] is false. Motivated by this somewhat negative result, we study whether it is possible to obtain a better approximation for specific cases. For unweighted directed or undir ected graphs, we show that if D = 3h + z, where h ≥ 0 and z ∈ {0,1,2}, then it is possible to report in ˜ O(min{m 2/3 n 4/3 ,m 2 1/(2h+3) }) time an estimate ˆ

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)