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: "dynamic planar voronoi diagrams for general distance functions and their algorithmic applications"
  Abstract: We describe a new data structure for dynamic nearest neighbor queries in the plane with respect to a general family of distance functions that includes $L_p$-norms and additively weighted Euclidean distances, and for general (convex, pairwise disjoint) sites that have constant description complexity (line segments, disks, etc.). Our data structure has a polylogarithmic update and query time, improving an earlier data structure of Agarwal, Efrat and Sharir that required $O(n^\varepsilon)$ time for an update and $O(\log n)$ time for a query. Our data structure has numerous applications, and in all of them it gives faster algorithms, typically reducing an $O(n^\varepsilon)$ factor in the bounds to polylogarithmic. To further demonstrate its power, we give here two new applications: an efficient construction of a spanner in a disk intersection graph, and a data structure for efficient connectivity queries in a dynamic disk graph.

Connected through hyperedge HE-1 (induced by source paper "a graph theoretic additive approximation of optimal transport"):
  with members:
    - "on efficient optimal transport an analysis of greedy and accelerated mirror descent algorithms"
    - "preconditioning for the geometric transportation problem"
    - "computational optimal transport complexity by accelerated gradient descent is better than by sinkhorn s algorithm"
    - "towards optimal running times for optimal transport"
    - "approximating optimal transport with linear programs"
    - "a faster algorithm for minimum cost bipartite matching in minor free graphs"
    - "approximating the quadratic transportation metric in near linear time"
    - "near linear time approximation algorithms for optimal transport via sinkhorn iteration"

Connected through hyperedge HE-2 (induced by source paper "euclidean tsp motorcycle graphs and other new applications of nearest neighbor chains"):
  with members:
    - "faster algorithms for some optimization problems on collinear points"
    - "the approximation ratio of the greedy algorithm for the metric traveling salesman problem"
    - "a stable marriage requires communication"
    - "general auction mechanism for search advertising"
    - "simple distributed weighted matchings"

Connected through hyperedge HE-3 (induced by source paper "efficient algorithms for geometric partial matching"):
  with members:
    - "preconditioning for the geometric transportation problem"
    - "faster algorithms for the geometric transportation problem"
    - "scaling algorithms for weighted matching in general graphs"
    - "navigating central path with electrical flows from flows to matchings and back"

Connected through hyperedge HE-4 (induced by source paper "maximum matchings in geometric intersection graphs"):
  with members:
    - "triangles and girth in disk graphs and transmission graphs"
    - "approximation algorithms for polynomial expansion and low density graphs"
    - "a simplication of the mv matching algorithm and its proof"
    - "navigating central path with electrical flows from flows to matchings and back"

Connected through hyperedge HE-5 (induced by source paper "faster algorithms for the geometric transportation problem"):
  with members:
    - "fast optimal transport averaging of neuroimaging data"
    - "parallel algorithms for geometric graph problems"
    - "fast construction of nets in low dimensional metrics and their applications"

Connected through hyperedge HE-6 (induced by source paper "thaad efficient matching queries under temporal abstraction for anomaly detection"):
  with members:
    - "euclidean tsp motorcycle graphs and other new applications of nearest neighbor chains"
    - "dynamic geometric data structures via shallow cuttings"
    - "a survey on learning to hash"

Connected through hyperedge HE-7 (induced by source paper "dynamic geometric data structures via shallow cuttings"):
  with members:
    - "faster fully dynamic minimum spanning forest"
    - "orthogonal range searching on the ram revisited"
    - "fast hierarchical clustering and other applications of dynamic closest pairs"

Connected through hyperedge HE-8 (induced by source paper "maintaining the union of unit discs under insertions with near optimal overhead"):
  with members:
    - "sensory regimes of effective distributed searching without leaders"
    - "fine grained complexity analysis of two classic tsp variants"

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)