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: "convex hull of points lying on lines in o nlogn time after preprocessing"
  Abstract: Motivated by the desire to cope with data imprecision Loffler (2009) [31], we study methods for taking advantage of preliminary information about point sets in order to speed up the computation of certain structures associated with them. In particular, we study the following problem: given a set L of n lines in the plane, we wish to preprocess L such that later, upon receiving a set P of n points, each of which lies on a distinct line of L, we can construct the convex hull of P efficiently. We show that in quadratic time and space it is possible to construct a data structure on L that enables us to compute the convex hull of any such point set P in O([email protected](n)log^@?n) expected time. If we further assume that the points are ''oblivious'' with respect to the data structure, the running time improves to O([email protected](n)). The same result holds when L is a set of line segments (in general position). We present several extensions, including a trade-off between space and query time and an output-sensitive algorithm. We also study the ''dual problem'' where we show how to efficiently compute the (=

Connected through hyperedge HE-1 (induced by source paper "a framework for robust realistic geometric computations"):
  with members:
    - "chirotopes of random points in space are realizable on a small integer grid"
    - "smoothed analysis of order types"
    - "optimal curve straightening is exists mathbb r complete"
    - "beyond worst case analysis"
    - "the complexity of drawing a graph in a polygonal region"
    - "on order types of random point sets"
    - "on the complexity of minimum link path problems"
    - "recognition and complexity of point visibility graphs"

Connected through hyperedge HE-2 (induced by source paper "unions of onions preprocessing imprecise points for fast onion decomposition"):
  with members:
    - "halving balls in deterministic linear time"
    - "self improving algorithms"

Connected through hyperedge HE-3 (induced by source paper "sharp bounds on davenport schinzel sequences of every order"):
  with members:
    - "complexity of a single face in an arrangement of s intersecting curves"
    - "convex hull of imprecise points in o n log n time after preprocessing"
    - "largest empty circle centered on a query line"
    - "a kinetic triangulation scheme for moving points in the plane"
    - "improved bounds and new techniques for davenport schinzel sequences and their generalizations"
    - "querying two boundary points for shortest paths in a polygonal domain"
    - "splay trees davenport schinzel sequences and the deque conjecture"

Connected through hyperedge HE-4 (induced by source paper "self improving algorithms for coordinate wise maxima and convex hulls"):
  with members:
    - "instance optimal geometric algorithms"
    - "convex hull of imprecise points in o n log n time after preprocessing"
    - "self improving algorithms"
    - "odds on trees"

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)