Index tuning for query-log based on-line index maintenance

The existing query-log based on-line index maintenance approaches rely on frequency distribution of terms in the static query-log. Though these approaches are proved to be efficient, but in real world, the frequency distribution of the terms changes over a period of time. This negatively affects the efficiency of the static query-log based approaches. To overcome this problem, we propose an index tuning strategy for reorganizing the indexes according to the latest frequency distribution of the terms captured from query-logs.Experimental results show that the proposed tuning strategy improves the performance of static query-log based approaches.