摘要: The queries in Online Analytical Processing (OLAP) are user-guided. OLAP is based on a multidimensional data model for complex analytical and ad-hoc with rapid execution time. Those either routed or on-demand revolved around the task. Most such reusable optimized system. Therefore, recorded query logs completing various tasks may be reusable. usually contain sequence of SQL that show action flows users their preference, interests, behaviours during action. This research investigates feature extraction to identify patterns user from historical logs. expected results will used recommend forthcoming help decision makers analysis. purpose this work improve efficiency effectiveness terms computation cost response Furthermore, proposed system able adjust some parameters finding common different make recommendation flexible user-adaptive.
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