User-Specified Conditional Preferences Driven Personalized Skyline Web Services Selection
Ke Song, Xiaodong Fu · 2024
The proliferation of web services with similar functionalities challenges selecting the most relevant service based on Quality of Service (QoS). Skyline queries help by reducing the candidate pool, but the resulting service skyline can still be extensive, making selection difficult. A personalized Skyline service selection method provides a smaller, more manageable set. Current approaches often overlook inter-dependencies between user preferences, complicating complex preference management. This paper introduces CP-Skyline, an efficient method leveraging Conditional Preference Networks (CP-Nets) to incorporate user-specific preferences and personalize the service selection process. We present a personalized conditional preference model based on CP-Nets to prune candidate services and compress the query space, defining a new dominance relation for CP-Skyline computation, and validate our approach through extensive experiments on synthetic and real-world datasets.