Julien Aligon

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OLAP queries are not normally formulated in isolation, but in the form of sequences called OLAP sessions. Recognizing that two OLAP sessions are similar would be useful for different applications, such as query recommendation and personalization; however, the problem of measuring OLAP session similarity has not been studied so far. In this paper, we aim at(More)
While OLAP has a key role in supporting effective exploration of multidimensional cubes, the huge number of aggregations and selections that can be operated on data may make the user experience disorientating. To address this issue, in the paper we propose a recommendation approach stemming from collaborative filtering. We claim that the whole sequence of(More)
The goal of personalization is to deliver information that is relevant to an individual or a group of individuals in the most appropriate format and layout. In the OLAP context personalization is quite beneficial, because queries can be very complex and they may return huge amounts of data. Aimed at making the user’s experience with OLAP as plain as(More)
Résumé. Une façon d’assister l’analyse d’entrepôt de données repose sur l’exploitation et la fouille de fichiers logs de requêtes OLAP. Mais, à notre connaissance, il n’existe pas de méthode permettant d’obtenir une représentation d’un tel log qui soit à la fois concise et exploitable. Dans ce papier, nous proposons une méthode pour résumer et interroger(More)
Leveraging query logs benefits the users analyzing large data warehouses. But so far nothing exists to allow the user to have concise and usable representation of what is in the log. In this paper, we propose a framework for summarizing OLAP query logs. This framework is based on the idea that a query can summarize another query and that a log can summarize(More)
This paper proposes a manipulation language tailored for OLAP query logs, stemming from the relational algebra. This language is based on binary relations over sequences of queries (called sessions). We propose two such relations allowing to group and order sessions. Examples of expressions in this language illustrate its interest for various user-centric(More)
It is quite common these days for experts, casual analysts, executives or data enthusiasts, to analyze large datasets using userfriendly interfaces on top of Business Intelligence (BI) systems. However, current BI systems do not adequately detect and characterize user interests, which may lead to tedious and unproductive interactions. In this paper, we(More)
OLAP is the main paradigm for flexible and effective exploration of multidimensional cubes in data warehouses. During an OLAP session the user analyzes the results of a query and determines a new query that will give her a better understanding of information. Given the huge size of the data space, this exploration process is often tedious and may leave the(More)