  In order to provide suitable results to the analyst needs, user preferences
summarization is widely used in several domains. In this paper, we introduce a
new approach for user profile construction from OLAP query logs. The key idea
is to learn the user's preferences by drawing the evidence from OLAP logs. In
fact, the analyst preferences are clustered into three main pools : (i)
consensual or non conflicting preferences referring to same preferences for all
analysts; (ii) semi-conflicting preferences corresponding to similar
preferences for some analysts; (iii) conflicting preferences related to
disjoint preferences for all analysts. To build generic and global model
accurately describing the analyst, we enrich the obtained characteristics
through including several views, namely the personal view, the professional
view and the behavioral view. After that, the multiview profile extracted from
multidimensional database can be annotated.
