Recommending Improved Configurations for Complex Objects with an Application in Travel Planning

In many applications a user attempts to configure a complex object with many possible internal choices. Recommendation engines that automatically configure such objects given user preferences and constraints, may provide much value in such cases. These applications offer the user various methods to provide the input and generate appropriate recommendations. It is likely, though, that the user will not be able to fully express her preferences and constraints, requiring a phase of manual tuning of the recommended configuration. We suggest that following this manual revision, additional constraints and preferences can be automatically collected, and the recommended configuration can be automatically improved. Specifically, we suggest a recommender component that takes as input an initial manual configuration of a complex object, deduces certain user preferences and constraints from this configuration, and constructs an alternative configuration. We show an appealing application for our method in complex trip planning, and demonstrate its usability in a user study.