A strong-dominance-based approach for refining the skyline
Hamiche Mahmoud, Habiba Drias, Allel Hadjali · 2015
This paper addresses the problem of refining large skylines by introducing a new dominance relationship. Skyline queries are powerful tool to capture user preferences. However in some contexts, the skyline is too large to give any useful insight to the user. In order to solve this problem, we introduce a strong dominance relationship that relies on the relation called “much preferred”. This leads to a new extension called MPS (Must Preferred Skyline) to find the most interesting skyline tuples. Furthermore, we propose a new algorithm to compute MPS efficiently. Extensive experiments demonstrate the effectiveness of our extension and the performance of the proposed algorithm.