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: "form function optimizing aesthetic product design via adaptive geometrized preference elicitation"
  Abstract: Visual design is critical to product success, and the subject of intensive marketing research effort. Yet visual elements, due to their holistic and interactive nature, do not lend themselves well to optimization using extant decompositional methods for preference elicitation. Here we present a systematic methodology to incorporate interactive, 3D-rendered product configurations into a conjoint-like framework. The method relies on rapid, scalable machine learning algorithms to adaptively update product designs along with standard information-oriented product attributes. At its heart is a parametric account of a product's geometry, along with a novel, adaptive "bi-level" query task that can estimate individuals' visual design form preferences and their trade-offs against such traditional elements as price and product features. We illustrate the method's performance through extensive simulations and robustness checks, a formal proof of the bi-level query methodology's domain of superiority, and a field test for the design of a mid-priced sedan, using real-time 3D rendering for an online panel. Results indicate not only substantially enhanced predictive accuracy, but two quantities beyond the reach of standard conjoint methods: trade-offs between form and function overall, and willingness-to-pay for specific design elements. Moreover -- and most critically for applications -- the method provides "optimal" visual designs for both individuals and model-derived or analyst-supplied consumer groupings, as well as their sensitivities to form and functional elements.

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.HC(Human-Computer Interaction)