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: "quantitative comparison of time dependent treemaps"
  Abstract: Rectangular treemaps are often the method of choice for visualizing large hierarchical datasets. Nowadays such datasets are available over time, and hence there is a need for (a) treemapping algorithms that can handle time-dependent data, and (b) corresponding quality criteria and evaluations. In recent years a wide variety of treemapping algorithms and corresponding quality criteria have been proposed, each with their own advantages and limitations, which are often hard to judge and compare. We aim to provide insights to allow researchers and practitioners to make an informed choice when selecting a treemapping algorithm for their specific application and their data. For this, we perform an extensive quantitative evaluation of rectangular treemapping algorithms for time-dependent data. As part of this evaluation we propose a novel classification scheme for time-dependent tree datasets. We approximate the infinite problem space of all such datasets by a low-dimensional feature space spanned by measurable characteristics (features) of the problem instances. We propose four such features to characterize time-dependent hierarchical datasets and classify all datasets used in our experiments accordingly. Moreover, we introduce a new method to measure the stability of time-dependent treemaps which explicitly incorporates the change in the input data. We analyze and visually summarize the results with respect to both visual quality and stability. All datasets, metrics, and algorithms are openly available to facilitate reuse and further comparative studies.

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)