human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "distance sensitive planar point location"):
  Abstract: Let S be a connected planar polygonal subdivision with n edges that we want to preprocess for point-location queries, and where we are given the probability γ i that the query point lies in a polygon P i of S . We show how to preprocess S such that the query time for a point p ? P i depends on γ i and, in addition, on the distance from p to the boundary of P i -the further away from the boundary, the faster the query. More precisely, we show that a point-location query can be answered in time O ( min ? ( log ? n , 1 + log ? area ( P i ) γ i Δ p 2 ) ) , where Δ p is the shortest Euclidean distance of the query point p to the boundary of P i . Our structure uses O ( n ) space and O ( n log ? n ) preprocessing time. It is based on a decomposition of the regions of S into convex quadrilaterals and triangles with the following property: for any point p ? P i , the quadrilateral or triangle containing p has area ? ( Δ p 2 ) . For the special case where S is a subdivision of the unit square and γ i = area ( P i ) , we present a simpler solution that achieves a query time of O ( min ? ( log ? n , log ? 1 Δ p 2 ) ) . The latter solution can be extended to convex subdivisions in three dimensions.

Includes members:
  Member "entropy triangulation and point location in planar subdivisions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "dynamic distribution sensitive point location")
  Member "a static optimality transformation with applications to planar point location":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the online min sum set cover problem")
  Member "adaptive uncertainty resolution in bayesian combinatorial optimization problems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the markovian price of information")

Question: Please tell me which class the source paper 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)