A Novel Approach to Query Modification Based on User’s Why-not Question

Top-k query is an efficient way to show the most important objects to user from massive amounts of data. After huge effort working on database performance, recently, an explain capability has attract more attention in recent years. In top-k query, since people may not specify his/her accurate preference, he may feel frustrated with the top-k results and propose a question such that “why my expecting tuple is not appeared in top-k results as long as tuple p has been appeared in top-k results”. Based on this motivation, in this paper, we propose a new method to approach this problem. Given the inputs as the original top-k query, the expecting tuple and the comparable tuple, our algorithm returns a new query to the user which makes the smallest change in the original top-k results. Finally, an extensive performance study using both synthetic and real data set is reported to verify its effectiveness and efficiency.