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: "entropy triangulation and point location in planar subdivisions"
  Abstract: A data structure is presented for point location in connected planar subdivisions when the distribution of queries is known in advance. The data structure has an expected query time that is within a constant factor of optimal. More specifically, an algorithm is presented that preprocesses a connected planar subdivision G of size n and a query distribution D to produce a point location data structure for G. The expected number of point-line comparisons performed by this data structure, when the queries are distributed according to D, is H + O(H1/2+1) where H=H(G,D) is a lower bound on the expected number of point-line comparisons performed by any linear decision tree for point location in G under the query distribution D. The preprocessing algorithm runs in O(n log n) time and produces a data structure of size O(n). These results are obtained by creating a Steiner triangulation of G that has near-minimum entropy.

Connected through hyperedge HE-1 (induced by source paper "dynamic distribution sensitive point location"):
  with members:
    - "point location in incremental planar subdivisions"
    - "point location in dynamic planar subdivisions"
    - "adaptive planar point location"
    - "instance optimal geometric algorithms"
    - "a static optimality transformation with applications to planar point location"
    - "odds on trees"

Connected through hyperedge HE-2 (induced by source paper "distance sensitive planar point location"):
  with members:
    - "a static optimality transformation with applications to planar point location"
    - "adaptive uncertainty resolution in bayesian combinatorial optimization problems"

Connected through hyperedge HE-3 (induced by source paper "instance optimal geometric algorithms"):
  with members:
    - "self improving algorithms"
    - "odds on trees"
    - "biased range trees"
    - "optimal adaptive algorithms for finding the nearest and farthest point on a parametric black box curve"
    - "optimal aggregation algorithms for middleware"
    - "smoothed analysis of algorithms why the simplex algorithm usually takes polynomial time"
    - "dense point sets have sparse delaunay triangulations"

Connected through hyperedge HE-4 (induced by source paper "a static optimality transformation with applications to planar point location"):
  with members:
    - "improved upper bounds for pairing heaps"
    - "self improving algorithms"
    - "point location in disconnected planar subdivisions"
    - "odds on trees"
    - "layered working set trees"

Connected through hyperedge HE-5 (induced by source paper "point location in disconnected planar subdivisions"):
  with members:
    - "biased range trees"

Connected through hyperedge HE-6 (induced by source paper "odds on trees"):
  with members:
    - "biased range trees"

Connected through hyperedge HE-7 (induced by source paper "biased range trees"):
  with members:
    - "instance optimal geometric algorithms"

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)