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: "randomized incremental construction for the hausdorff voronoi diagram revisited and extended"
  Abstract: The Hausdorff Voronoi diagram of clusters of points in the plane is a generalization of Voronoi diagrams based on the Hausdorff distance function. Its combinatorial complexity is \(O(n+m)\), where n is the total number of points and \(m\) is the number of crossings between the input clusters (\(m=O(n^2)\)); the number of clusters is k. We present efficient algorithms to construct this diagram following the randomized incremental construction (RIC) framework (Clarkson and Shor in Discrete Comput Geom 4:387–421, 1989; Clarkson et al. in Comput Geom Theory Appl 3(4):185–212, 1993). Our algorithm for non-crossing clusters (\(m=0\)) runs in expected \(O(n\log {n} + k\log n \log k)\) time and deterministic O(n) space. The algorithm for arbitrary clusters runs in expected \(O((m+n\log {k})\log {n})\) time and \(O(m+n\log {k})\) space. The two algorithms can be combined in a crossing-oblivious scheme within the same bounds. We show how to apply the RIC framework to handle non-standard characteristics of generalized Voronoi diagrams, including sites (and bisectors) of non-constant complexity, sites that are not enclosed in their Voronoi regions, empty Voronoi regions, and finally, disconnected bisectors and disconnected Voronoi regions. The Hausdorff Voronoi diagram finds direct applications in VLSI CAD.

Connected through hyperedge HE-1 (induced by source paper "searching edges in the overlap of two plane graphs"):
  with members:
    - "a randomized incremental algorithm for the hausdorff voronoi diagram of non crossing clusters"
    - "farthest polygon voronoi diagrams"
    - "data structures for halfplane proximity queries and incremental voronoi diagrams"

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)