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: "multidimensional β skeletons in l_1 and l_ infty metric"
  Abstract: The $\beta$-skeleton $\{G_{\beta}(V)\}$ for a point set V is a family of geometric graphs, defined by the notion of neighborhoods parameterized by real number $0 < \beta < \infty$. By using the distance-based version definition of $\beta$-skeletons we study those graphs for a set of points in $\mathbb{R}^d$ space with $l_1$ and $l_{\infty}$ metrics. We present algorithms for the entire spectrum of $\beta$ values and we discuss properties of lens-based and circle-based $\beta$-skeletons in those metrics. #R##N#Let $V \in \mathbb{R}^d$ in $L_{\infty}$ metric be a set of $n$ points in general position. Then, for $\beta<2$ lens-based $\beta$-skeleton $G_{\beta}(V)$ can be computed in $O(n^2 \log^d n)$ time. For $\beta \geq 2$ there exists an $O(n \log^{d-1} n)$ time algorithm that constructs $\beta$-skeleton for the set $V$. We show that in $\mathbb{R}^d$ with $L_{\infty}$ metric, for $\beta<2$ $\beta$-skeleton $G_{\beta}(V)$ for $n$ points can be computed in $O(n^2 \log^d n)$ time. For $\beta \geq 2$ there exists an $O(n \log^{d-1} n)$ time algorithm. In $\mathbb{R}^d$ with $L_1$ metric for a set of $n$ points in arbitrary position $\beta$-skeleton $G_{\beta}(V)$ can be computed in $O(n^2 \log^{d+2} n)$ time.

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)