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: "products of euclidean metrics and applications to proximity questions among curves"
  Abstract: The problem of Approximate Nearest Neighbor (ANN) search is fundamental in computer science and has benefited from significant progress in the past couple of decades. However, most work has been devoted to pointsets whereas complex shapes have not been sufficiently treated. Here, we focus on distance functions between discretized curves in Euclidean space: they appear in a wide range of applications, from road segments to time-series in general dimension. For $\ell_p$-products of Euclidean metrics, for any $p$, we design simple and efficient data structures for ANN, based on randomized projections, which are of independent interest. They serve to solve proximity problems under a notion of distance between discretized curves, which generalizes both discrete Fr\'{e}chet and Dynamic Time Warping distances. These are the most popular and practical approaches to comparing such curves. We offer the first data structures and query algorithms for ANN with arbitrarily good approximation factor, at the expense of increasing space usage and preprocessing time over existing methods. Query time complexity is comparable or significantly improved by our algorithms; our algorithm is especially efficient when the length of the curves is bounded.

Connected through hyperedge HE-1 (induced by source paper "dynamic time warping in strongly subquadratic time algorithms for the low distance regime and approximate evaluation"):
  with members:
    - "the one way communication complexity of dynamic time warping distance"
    - "approximating edit distance within constant factor in truly sub quadratic time"
    - "on estimating edit distance alignment dimension reduction and embeddings"
    - "locality sensitive hashing of curves"
    - "streaming algorithms for computing edit distance without exploiting suffix trees"
    - "dynamic time warping and geometric edit distance breaking the quadratic barrier"
    - "quadratic conditional lower bounds for string problems and dynamic time warping"
    - "approximating dynamic time warping and edit distance for a pair of point sequences"

Connected through hyperedge HE-2 (induced by source paper "the one way communication complexity of dynamic time warping distance"):
  with members:
    - "locality sensitive hashing of curves"
    - "edit distance sketching streaming and document exchange"
    - "dynamic time warping and geometric edit distance breaking the quadratic barrier"
    - "efficient deterministic single round document exchange for edit distance"
    - "quadratic conditional lower bounds for string problems and dynamic time warping"
    - "approximating dynamic time warping and edit distance for a pair of point sequences"
    - "sparsedtw a novel approach to speed up dynamic time warping"
    - "voice recognition algorithms using mel frequency cepstral coefficient mfcc and dynamic time warping dtw techniques"

Connected through hyperedge HE-3 (induced by source paper "sublinear data structures for short fr echet queries"):
  with members:
    - "the one way communication complexity of dynamic time warping distance"
    - "approximate nearest neighbor for curves simple efficient and deterministic"
    - "on optimal polyline simplification using the hausdorff and fr echet distance"
    - "a fast implementation of near neighbors queries for frechet distance gis cup"
    - "on the complexity of range searching among curves"
    - "coresets and sketches"
    - "why walking the dog takes time frechet distance has no strongly subquadratic algorithms unless seth fails"
    - "fast construction of nets in low dimensional metrics and their applications"

Connected through hyperedge HE-4 (induced by source paper "approximate nearest neighbor for curves simple efficient and deterministic"):
  with members:
    - "sublinear data structures for short fr echet queries"
    - "nonlinear dimension reduction via outer bi lipschitz extensions"
    - "optimal terminal dimensionality reduction in euclidean space"
    - "locality sensitive hashing of curves"
    - "on the complexity of range searching among curves"
    - "why walking the dog takes time frechet distance has no strongly subquadratic algorithms unless seth fails"
    - "faster retrieval with a two pass dynamic time warping lower bound"

Connected through hyperedge HE-5 (induced by source paper "efficient nearest neighbor query and clustering of planar curves"):
  with members:
    - "locality sensitive hashing of curves"
    - "on the complexity of range searching among curves"
    - "spatio temporal analysis of team sports"
    - "why walking the dog takes time frechet distance has no strongly subquadratic algorithms unless seth fails"
    - "computing the discrete fr echet distance in subquadratic time"

Connected through hyperedge HE-6 (induced by source paper "the vc dimension of metric balls under fr echet and hausdorff distances"):
  with members:
    - "a fast implementation of near neighbors queries for frechet distance gis cup"
    - "on the complexity of range searching among curves"
    - "spatio temporal analysis of team sports"
    - "a new upper bound for the vc dimension of visibility regions"

Connected through hyperedge HE-7 (induced by source paper "fresh fr echet similarity with hashing"):
  with members:
    - "approximate nearest neighbor search in high dimensions"
    - "a fast implementation of near neighbors queries for frechet distance gis cup"
    - "locality sensitive hashing of curves"
    - "on the complexity of range searching among curves"
    - "fast locality sensitive hashing for approximate near neighbor search"
    - "fast locality sensitive hashing frameworks for approximate near neighbor search"
    - "spatio temporal analysis of team sports"
    - "parameter free locality sensitive hashing for spherical range reporting"

Connected through hyperedge HE-8 (induced by source paper "probabilistic embeddings of the fr echet distance"):
  with members:
    - "on the complexity of range searching among curves"
    - "dynamic time warping and geometric edit distance breaking the quadratic barrier"
    - "quadratic conditional lower bounds for string problems and dynamic time warping"
    - "approximating dynamic time warping and edit distance for a pair of point sequences"
    - "quadratic time hardness of lcs and other sequence similarity measures"
    - "why walking the dog takes time frechet distance has no strongly subquadratic algorithms unless seth fails"
    - "on the impossibility of dimension reduction for doubling subsets of ell_p p 2"
    - "four soviets walk the dog with an application to alt s conjecture"

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)