| 摘要 |
A system and method for problem solving in multiple domains on the web is provided. Two facets of preference are applied regardless of domain: first, criteria selected by the user which indicates which elements relate to the user, and second, level of importance to the user. For each decision aid that the user saves to his/her member account, a series of methods applied thereto assist the user in making decisions through intelligent agent expertise, as well as through related eCommerce, social networking, guided content search and delivery of context-rich content. Relevancy of results is also calculated. Depending on characteristics inherent in a particular domain, one of two primary methods is employed. The Multi-Product method uses ontology and a neural network engine to reveal the subset of relevant results based on any combination of user inputs, implicitly and explicitly derived. The Single-Product method maps inputs to results using sub-category analysis of fit and then applies user-centric filters and discounting rules to return meaningful coaching and relevancy of results. |
