Handling Qualitative and Quantitative Preferences with Constraints in Interactive Applications
MetadataShow full item record
Preference elicitation is very important for interactive systems. A potential buyer typically has speci c expectations in the attributes of the product he or she is interested in. While the current interactive systems allow users to provide some keywords and other information in order to lter and obtain only what they need, users feel the product they get does not necessarily meet their satisfaction. This thesis proposes a new interactive system that enables buyers to express their needs and desires. Users are given the ability to elicit their requirements and preferences in a friendly and interactive way. The system will then provide a list of suggestions satisfying user requirements and maximizing desires. Requirements and preferences are managed respectively as a set of hard constraints and soft constraints where the latter can be quantitative (numerical), qualitative (ordinal), or both. This is an optimization problem where the optimal solutions (best outcomes) are those satisfying hard constraints and maximizing user preferences. We use the C-semiring and the CP-net to represent the set of quantitative and qualitative preferences respectively. The branch and bound method is then applied in order to provide the users with a list of Pareto optimal outcomes satisfying the hard constraints and optimizing the preferences. We use approximation techniques in order to convert conditional and qualitative preferences to soft constraints. The proposed interactive system is enhanced with a component that learns from other buyer preferences and makes a set of recommendations using data mining techniques including classi cation, association rules, and cluster analysis. High- delity prototyping, an evaluation framework, and a Volere requirements speci cation template are used in order to obtain user feedback on the interactive design for the proposed system. For better management of constraints and preferences, the well-known constrained CP-Net model is extended to quantitative constraints. This extended model, named weighted constrained CP-net, takes a set of constraints and preferences expressing user requirements and desires. It then returns a set of outcomes provided in the form of a list of suggestions. The results of experimental tests, conducted to evaluate the performance of the interactive system, are very promising.