Query recommendations for OLAP discovery driven analysis

Recommending database queries is an emerging and promising field of investigation. This is of particular interest in the domain of OLAP systems where the user is left with the tedious process of navigating large datacubes. In this paper we present a framework for a recommender system for OLAP users, that leverages former users’ investigations to enhance discovery driven analysis. The main idea is to recommend to the user the discoveries detected in those former sessions that investigated the same unexpected data as the current session. Categories and Subject Descriptors H.2.7 [Database Administration]: Data warehouse and repository; H.3.3 [Information Search and Retrieval]: Query formulation General Terms Algorithms, Design Keywords OLAP analysis, MDX queries, recommendation

• Type: Conference
• Year: 2009
• Where: DOLAP
• Authors: Arnaud Giacometti, Patrick Marcel, Elsa Negre, Arnaud Soulet
• Keywords: Discovery Driven Analysis, DOLAP 2009, Information Management, Keywords OLAP Analysis, OLAP