When issuing user-specific queries, users often present vague and imprecise information needs. Skyline queries with an intuitive query formulation mechanism identify the most interesting objects for incomplete user preferences. However, the applicability of skyline queries suffers from a severe drawback because incomplete user preferences often lead to an impractical skyline size. To address this problem, we develop an interactive preference elicitation framework - while user preferences are collected at each iteration, the framework iteratively updates skylines. In this process, the framework aims to both minimize user interaction and maximize skyline reduction size, while the query formulation is still intuitive. All that users need to do is thus to answer a few well-chosen questions generated from the framework. We validate the effectiveness and efficiency of our framework in extensive experimental settings, and demonstrate that a few questions are enough to acquire a skyline with a manageable size.
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Theoretical Computer Science
- Computer Science Applications
- Information Systems and Management
- Artificial Intelligence