作者
Arnaud Giacometti, Patrick Marcel, Elsa Negre, Arnaud Soulet
发表日期
2009/11/6
研讨会论文
Proceedings of the ACM twelfth international workshop on Data warehousing and OLAP
页码范围
81-88
出版商
ACM
简介
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.
学术搜索中的文章
A Giacometti, P Marcel, E Negre, A Soulet - Proceedings of the ACM twelfth international workshop …, 2009