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In order to provide suitable results to the analyst needs, user preferencessummarization is widely used in several domains. In this paper, we introduce anew approach for user profile construction from OLAP query logs. The key ideais to learn the user's preferences by drawing the evidence from OLAP logs. Infact, the analyst preferences are clustered into three main pools : (i)consensual or non conflicting preferences referring to same preferences for allanalysts; (ii) semi-conflicting preferences corresponding to similarpreferences for some analysts; (iii) conflicting preferences related todisjoint preferences for all analysts. To build generic and global modelaccurately describing the analyst, we enrich the obtained characteristicsthrough including several views, namely the personal view, the professionalview and the behavioral view. After that, the multiview profile extracted frommultidimensional database can be annotated.

Building MultiView Analyst Profile From Multidimensional Query Logs: From Consensual to Conflicting Preferences