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 "clustering time series under the fr echet distance"):
  Abstract: The Fr\'echet distance is a popular distance measure for curves. We study the problem of clustering time series under the Fr\'echet distance. In particular, we give $(1+\varepsilon)$-approximation algorithms for variations of the following problem with parameters $k$ and $\ell$. Given $n$ univariate time series $P$, each of complexity at most $m$, we find $k$ time series, not necessarily from $P$, which we call \emph{cluster centers} and which each have complexity at most $\ell$, such that (a) the maximum distance of an element of $P$ to its nearest cluster center or (b) the sum of these distances is minimized. Our algorithms have running time near-linear in the input size for constant $\varepsilon$, $k$ and $\ell$. To the best of our knowledge, our algorithms are the first clustering algorithms for the Fr\'echet distance which achieve an approximation factor of $(1+\varepsilon)$ or better. #R##N#Keywords: time series, longitudinal data, functional data, clustering, Fr\'echet distance, dynamic time warping, approximation algorithms.

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 "how good is the chord algorithm":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the power of the weighted sum scalarization for approximating multiobjective optimization problems")
  Member "on the impossibility of dimension reduction for doubling subsets of ell_p p 2":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "probabilistic embeddings of the fr echet distance")
  Member "approximating k median via pseudo approximation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "fair correlation clustering")
  Member "four soviets walk the dog with an application to alt s conjecture":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "fresh fr echet similarity with hashing")
  Member "jaywalking your dog computing the fr echet distance with shortcuts":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on the chain pair simplification problem")
  Member "a unified framework for approximating and clustering data":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "approximating spectral clustering via sampling a review")
  Member "approximating the fr echet distance for realistic curves in near linear time":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "jaywalking your dog computing the fr echet distance with shortcuts")

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)