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 "a fast implementation of near neighbors queries for frechet distance gis cup"):
  Abstract: This paper describes an implementation of fast near-neighbours queries (also known as range searching) with respect to the Frechet distance. The algorithm is designed to be efficient on practical data such as GPS trajectories. Our approach is to use a quadtree data structure to enumerate all curves in the database that have similar start and endpoints as the query curve. On these curves we run positive and negative filters to narrow the set of potential results. Only for those trajectories where these heuristics fail, we compute the Frechet distance exactly, by running a novel recursive variant of the classic free-space diagram algorithm.   Our implementation is among the top 3 submissions to the ACM SIGSPATIAL GIS Cup 2017 (more specific standings will be available on the competition's website).

Includes members:
  Member "fr echet distance for curves revisited":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "tighter connections between formula sat and shaving logs")
  Member "why walking the dog takes time frechet distance has no strongly subquadratic algorithms unless seth fails":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "graphs cannot be indexed in polynomial time for sub quadratic time string matching unless seth fails")
  Member "four soviets walk the dog with an application to alt s conjecture":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fresh fr echet similarity with hashing")
  Member "can we compute the similarity between surfaces":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "computing the frechet distance of trees and graphs of bounded tree width")

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)