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Hdr Année : 2012

Leveraging query logs for user-centric OLAP

Résumé

OLAP (On-Line Analytical Processing), the process of efficiently enabling common analytical operations on the multidimensional view of data, is a corner stone of Business Intelligence. While OLAP is now a mature, efficiently implemented technology, very little attention has been paid to the effectiveness of the analysis and the user-friendliness of this technology, often considered tedious of use. This dissertation is a contribution to developing user-centric OLAP, focusing on the use of former queries logged by an OLAP server to enhance subsequent analyses. It shows how logs of OLAP queries can be modeled, constructed, manipulated, compared, and finally leveraged for personalization and recommendation. Logs are modeled as sets of analytical sessions, sessions being modeled as sequences of OLAP queries. Three main approaches are presented for modeling queries: as unevaluated collections of fragments (e.g., group by sets, sets of selection predicates, sets of measures), as sets of references obtained by partially evaluating the query over dimensions, or as query answers. Such logs can be constructed even from sets of SQL query expressions, by translating these expressions into a multidimensional algebra, and bridging the translations to detect analytical sessions. Logs can be searched, filtered, compared, combined, modified and summarized with a language inspired by the relational algebra and parametrized by binary relations over sessions. In particular, these relations can be specialization relations or based on similarity measures tailored for OLAP queries and analytical sessions. Logs can be mined for various hidden knowledge, that, depending on the query model used, accurately represents the user behavior extracted. This knowledge includes simple preferences, navigational habits and discoveries made during former explorations, and can be it used in various query personalization or query recommendation approaches. Such approaches vary in terms of formulation effort, proactiveness, prescriptiveness and expressive power: query personalization, i.e., coping with a current query too few or too many results, can use dedicated operators for expressing preferences, or be based on query expansion; query recommendation, i.e., suggesting queries to pursue an analytical session, can be based on information extracted from the current state of the database and the query, or be purely history based, i.e., leveraging the query log. While they can be immediately integrated into a complete architecture for User-Centric Query Answering in data warehouses, the models and approaches introduced in this dissertation can also be seen as a starting point for assessing the effectiveness of analytical sessions, with the ultimate goal to enhance the overall decision making process.
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Dates et versions

tel-01170937 , version 1 (06-07-2015)

Identifiants

  • HAL Id : tel-01170937 , version 1

Citer

Patrick Marcel. Leveraging query logs for user-centric OLAP. Computer Science [cs]. université de Tours, 2012. ⟨tel-01170937⟩
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