A knowledge-based framework for a mobile OLAP system Online publication date: Mon, 02-Feb-2015
by Nachida Rezoug; Omar Boussaid; Fahima Nader
International Journal of Decision Support Systems (IJDSS), Vol. 1, No. 1, 2015
Abstract: We propose in this paper a knowledge-based framework for a mobile OLAP. Its main goal is to allow decision-makers to, efficiently, access datasets in OLAP system anywhere and anytime. The challenge of this work is to be able to improve decisional performances while overcoming capability context. To achieve this goal, the framework integrates in a systematic, generic and extensible way, knowledge in the context-aware recommender process, on one hand. On the other hand, it proposes contextual recommendations. For that purpose, the context-aware recommender system exploits the knowledge extracted (profile in a particular situation 'contextual profile') automatically and the current user's contextual profile to compute a list of contextual recommendations (analysis) adapted to the capability context. We conducted a set of experiments to evaluate the performance of our knowledge-based framework. The results are encouraging and show that our framework contributes significantly to improve mobile OLAP navigation.
Online publication date: Mon, 02-Feb-2015
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Decision Support Systems (IJDSS):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email email@example.com