Approximating user preferences in online store systems

In many online systems, shoppers are usually overwhelmed by a huge number of outcomes and choices. In practice however, they usually have interest in only some of these choices. While these online shopping systems allow the users to provide some keywords and other information in order to filter and get only what they need, these latter feel that what they get does not necessarily meet their satisfaction. In this paper, we propose a new shopping system that enables the customers to express what they want when buying a product online. More precisely, the users are given the ability to provide their requirements and desires in a friendly and interactive way. The system will then provide a list of suggestions meeting the users´ requirements and maximizing their desires. Requirements and desires are managed, in a unique model, respectively as a set of hard constraints and preferences where these latter can be quantitative (numerical), qualitative (ordinal) or both. The branch and bound method is then applied in order to provide the users with a list of best outcomes.