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 "computing the frechet distance with a retractable leash"):
  Abstract: All known algorithms for the Frechet distance between curves proceed in two steps: first, they construct an efficient oracle for the decision version; second, they use this oracle to find the optimum from a finite set of critical values. We present a novel approach that avoids the detour through the decision version. This gives the first quadratic time algorithm for the Frechet distance between polygonal curves in $$\mathbb {R}^d$$Rd under polyhedral distance functions (e.g., $$L_1$$L1 and $$L_\infty $$L?). We also get a $$(1+\varepsilon )$$(1+?)-approximation of the Frechet distance under the Euclidean metric, in quadratic time for any fixed $$\varepsilon > 0$$?>0. For the exact Euclidean case, our framework currently yields an algorithm with running time $$O(n^2 \log ^2 n)$$O(n2log2n). However, we conjecture that it may eventually lead to a faster exact algorithm.

Includes members:
  Member "why walking the dog takes time frechet distance has no strongly subquadratic algorithms unless seth fails":
    also connected through other hyperedges:
      - Hyperedge HE-1 (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-2 (induced by source paper "fresh fr echet similarity with hashing")
  Member "locally correct frechet matchings":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "four soviets walk the dog improved bounds for computing the frechet distance")
  Member "geodesic fr echet distance inside a simple polygon":
    also connected through other hyperedges:
      (none)

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)