Query recommendations for OLAP discovery driven analysis

Authors:
Arnaud Giacometti;Patrick Marcel;Elsa Negre;Arnaud Soulet
Affiliations:
Université François Rabelais Tours, Tours, France;Université François Rabelais Tours, Tours, France;Université François Rabelais Tours, Tours, France;Université François Rabelais Tours, Tours, France
Venue:
Proceedings of the ACM twelfth international workshop on Data warehousing and OLAP
Year:
2009

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Abstract

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.