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: "an optimal hierarchical clustering approach to mobile lidar point clouds"
  Abstract: This paper aims to propose a new optimal hierarchical clustering approach to 3D mobile light detection and ranging (LiDAR) point clouds. The hierarchical clustering is performed on unorganized point clouds based on a proximity matrix that consists of a distance term and a direction term. In the dissimilarity calculation of two clusters, a pair of points from each of two clusters is selected, respectively, and Euclidean distances between the points are employed to define the distance term. The direction term is obtained by the differences of normal vectors at chosen points. The main contribution is that the cluster combination in the hierarchical clustering is optimized by a point-based graph model. The cluster combination is formulated as a problem of matching, optimized by finding the minimum-cost perfect matching in a bipartite graph. The results show that the proposed hierarchical clustering method succeeds in segmenting object from point clouds without any human-computer interaction and outperforms the state-of-the-art segmentation approaches in terms of completeness and correctness.

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.CV(Computer Vision and Pattern Recognition)