Personnalisation de Syst\`emes OLAP Annot\'es
Houssem Jerbi (IRIT), Genevi\`eve Pujolle (IRIT), Franck Ravat (IRIT),, Olivier Teste (IRIT)
TL;DR
This paper presents a personalized approach to annotated OLAP systems by extending data structures to incorporate annotations and user preferences, enhancing decision-making through contextual recommendations during multidimensional data navigation.
Contribution
It introduces a novel extension of OLAP data models to support annotations and user preferences, enabling personalized data exploration and decision support.
Findings
Enhanced decision-making with contextual recommendations
Support for annotations reflecting decision-maker experience
Improved user focus on relevant data during navigation
Abstract
This paper deals with personalization of annotated OLAP systems. Data constellation is extended to support annotations and user preferences. Annotations reflect the decision-maker experience whereas user preferences enable users to focus on the most interesting data. User preferences allow annotated contextual recommendations helping the decision-maker during his/her multidimensional navigations.
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Taxonomy
TopicsAdvanced Database Systems and Queries · Semantic Web and Ontologies · Data Management and Algorithms