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: "the k fr echet distance"
  Abstract: We introduce a new distance measure for comparing polygonal chains: the $k$-Fr\'echet distance. As the name implies, it is closely related to the well-studied Fr\'echet distance but detects similarities between curves that resemble each other only piecewise. The parameter $k$ denotes the number of subcurves into which we divide the input curves. The $k$-Fr\'echet distance provides a nice transition between (weak) Fr\'echet distance and Hausdorff distance. However, we show that deciding this distance measure turns out to be NP-complete, which is interesting since both (weak) Fr\'echet and Hausdorff distance are computable in polynomial time. Nevertheless, we give several possibilities to deal with the hardness of the $k$-Fr\'echet distance: besides an exponential-time algorithm for the general case, we give a polynomial-time algorithm for $k=2$, i.e., we ask that we subdivide our input curves into two subcurves each. We also present an approximation algorithm that outputs a number of subcurves of at most twice the optimal size. Finally, we give an FPT algorithm using parameters $k$ (the number of allowed subcurves) and $z$ (the number of segments of one curve that intersects the $\varepsilon$-neighborhood of a point on the other curve).

Connected through hyperedge HE-1 (induced by source paper "rock climber distance frogs versus dogs"):
  with members:
    - "four soviets walk the dog improved bounds for computing the frechet distance"
    - "recognizing weakly simple polygons"
    - "an optimal algorithm for minimum link rectilinear paths in triangulated rectilinear domains"
    - "detecting weakly simple polygons"
    - "why walking the dog takes time frechet distance has no strongly subquadratic algorithms unless seth fails"
    - "minimum link paths revisited"
    - "the problem of compatible representatives"

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)