Visual decision support system

This paper describes a visual decision support system that supports marketers in the advertising field. The purpose of this system is to help users estimate the effect of advertising based on the extraction of expert knowledge when there is no fresh data to go on. This system includes the following functions: a) To check the dispersion of data and the behavior of models using 3D plot displays, and b) To make prediction models capable of estimating the effect of advertising using a constrained learning algorithm for neural networks. These functions have each of the following features: a) The ability to easily check the dispersion of data and the behavior of models in the various axes, allowing a marketer to delete unnecessary data in 3D spaces. b) The basic premise that the relationship between the input and output monotonously increases. This system is useful for domains where only deficient data is available like estimating the effect of advertising. Experimental simulations using real data have shown that experts can easily check the dispersion of data and the behavior of models, and have shown that the algorithm makes more reasonable models for estimating the effect of advertising than other conventional algorithms.