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: "a static optimality transformation with applications to planar point location"
  Abstract: Over the last decade, there have been several data structures that, given a planar subdivision and a probability distribution over the plane, provide a way for answering point location queries that is fine-tuned for the distribution. All these methods suffer from the requirement that the query distribution must be known in advance. We present a new data structure for point location queries in planar triangulations. Our structure is asymptotically as fast as the optimal structures, but it requires no prior information about the queries. This is a 2-D analogue of the jump from Knuth's optimum binary search trees (discovered in 1971) to the splay trees of Sleator and Tarjan in 1985. While the former need to know the query distribution, the latter are statically optimal. This means that we can adapt to the query sequence and achieve the same asymptotic performance as an optimum static structure, without needing any additional information.

Connected through hyperedge HE-1 (induced by source paper "the online min sum set cover problem"):
  with members:
    - "chasing convex bodies optimally"
    - "stochastic online metric matching"
    - "pure entropic regularization for metrical task systems"
    - "metrical task systems on trees via mirror descent and unfair gluing"
    - "weighted k server bounds via combinatorial dichotomies"
    - "competitive algorithms for generalized k server in uniform metrics"
    - "the generalized work function algorithm is competitive for the generalized 2 server problem"
    - "a note on the generalized min sum set cover problem"

Connected through hyperedge HE-2 (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"
    - "entropy triangulation and point location in planar subdivisions"
    - "odds on trees"

Connected through hyperedge HE-3 (induced by source paper "distance sensitive planar point location"):
  with members:
    - "entropy triangulation and point location in planar subdivisions"
    - "adaptive uncertainty resolution in bayesian combinatorial optimization problems"

Connected through hyperedge HE-4 (induced by source paper "the power and limitations of static binary search trees with lazy finger"):
  with members:
    - "combining binary search trees"
    - "worst case optimal tree layout in external memory"

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)