A framework for recommending OLAP queries

A. Giacometti, Patrick Marcel, E. Negre
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引用次数: 66

Abstract

An OLAP analysis session can be defined as an interactive session during which a user launches queries to navigate within a cube. Very often choosing which part of the cube to navigate further, and thus designing the forthcoming query, is a difficult task. In this paper, we propose to use what the OLAP users did during their former exploration of the cube as a basis for recommending OLAP queries to the user. We present a generic framework that allows to recommend OLAP queries based on the OLAP server query log. This framework is generic in the sense that changing its parameters changes the way the recommendations are computed. We show how to use this framework for recommending simple MDX queries and we provide some experimental results to validate our approach.
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推荐OLAP查询的框架
可以将OLAP分析会话定义为交互式会话,在此会话中,用户启动查询以在多维数据集中导航。通常,选择要进一步导航多维数据集的哪个部分,从而设计即将到来的查询,是一项困难的任务。在本文中,我们建议使用OLAP用户在以前探索多维数据集期间所做的事情作为向用户推荐OLAP查询的基础。我们提出了一个通用框架,允许基于OLAP服务器查询日志推荐OLAP查询。这个框架是通用的,因为改变它的参数会改变计算推荐值的方式。我们展示了如何使用这个框架来推荐简单的MDX查询,并提供了一些实验结果来验证我们的方法。
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