| 摘要 |
A system and method generates recommendations of products or services to individuals. Product rankings by a large number of individuals are translated into approach and avoid response data for various categories of the products or services. The translated data is utilized to compute approach entropy values, avoid entropy values, mean approach intensity values, and mean avoid intensity values. One or more of a trade-off plot, a value function plot, and a saturation plot may be generated from the values. The plots may be analyzed to derive preference feature values. Clusters may be formed of individuals with the same preference feature values. Products or services that are highly ranked by members of a cluster may be recommended to other members of the cluster that have yet to purchase or consume the highly ranked products or services. |
