Cooperative query rewriting for decision making support and recommender systems

This article presents a new technology called interactive query management (IQM), designed for supporting flexible query management in decision support systems and recommender systems. IQM aims at guiding a user to refine a query to a structured repository of items when it fails to return a manageable set of products. Two failure conditions are considered here, when a query returns either too many products or no product at all. In the former case, IQM uses feature selection methods to suggest some features that, if used to further constrain the current query, would greatly reduce the result set size. In the latter case, the culprits of the failure are determined by a relaxation algorithm and explained to the user, enumerating the constraints that, if relaxed, would solve the '' no results '' problem. As a consequence, the user can understand the causes of the failure and decide what is the best query relaxation. After having presented IQM, we illustrate its empirical evaluation. We have conducted two types of experiments, with real users and offline simulations. Both validation procedures show that IQM can repair a large percentage of user queries and keep alive the human computer interaction until the user information goals are satisfied.