Management of context-aware preferences in multidimensional databases

Jerbi, Houssem; Ravat, Franck; Teste, Olivier; Zurfluh, Gilles

doi:10.1109/icdim.2008.4746714

Cited by 22 publications

(26 citation statements)

References 10 publications

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“…(ii) The second category expresses the knowledge seeker preferences using explicit behaviour modelling through personalized MDB schema [7] or an extension of MDX language as preference algebra [2].…”

Section: Related Workmentioning

confidence: 99%

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Building Con?ict-Aware Profiling Ontology from Data Warehouses

Ahmed¹,

Nabli²,

Gargouri³

2012

IJCA

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User profiles or user models are crucial in many areas in which it is essential to obtain knowledge about users of software applications such as data warehouse technologies. To enhance the personalized services, group profiles are derived through combining individual user profiles in order to represent group modelling. In this paper, we propose a new representation of group profiles in OLAP context using the ontological modelling. Our main aim is to semantically enrich the representation of group preferences in data warehouses. Our ontology is validated using set of real collected OLAP query logs in stock market area.

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Section: Related Workmentioning

confidence: 99%

“…Drawing decision marker profiles from data warehouses attracts a strong interest in data warehousing community during the last few years [2,3,6,7]. The discovered profiles sum up preferences closely related to the most occurring subschema in performed OLAP analysis.…”

Section: Introductionmentioning

confidence: 99%

Building Con?ict-Aware Profiling Ontology from Data Warehouses

Ahmed¹,

Nabli²,

Gargouri³

2012

IJCA

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“…Indeed, we cite the work of Jerbi et al (2008) that considers, in the field of profile-based personalisation (Stefanidis et al, 2009), that preferences are context-aware. However, the essence of context awareness is that items have different relevance depending on the context of analysis (Aligon et al, 2011a).…”

Section: Context-aware Recommender Systemsmentioning

confidence: 99%

“…However, the essence of context awareness is that items have different relevance depending on the context of analysis (Aligon et al, 2011a). Jerbi et al (2008) modelled a context as a tree of multidimensional analysis (fact, measure, dimensions, and parameters). In the same context [a profile-based personalisation (Stefanidis et al, 2009)], the work of Bellatreche et al (2006) presents a framework which allowed the OLAP system to adapt the data displayed, in data-cube, based on constrains (limits imposed by the device used to regulate the display format).…”

Section: Context-aware Recommender Systemsmentioning

confidence: 99%

“…In the same context [a profile-based personalisation (Stefanidis et al, 2009)], the work of Bellatreche et al (2006) presents a framework which allowed the OLAP system to adapt the data displayed, in data-cube, based on constrains (limits imposed by the device used to regulate the display format). But in both works (Jerbi et al, 2008;Bellatreche et al, 2006), the user profile and context are given (without indicating how they are constructed). We cite, also, the work of Golfarelli and Rizzi (2009) which expresses a user preferences, in OLAP queries, via a preference algebra.…”

Section: Context-aware Recommender Systemsmentioning

confidence: 99%

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A knowledge-based framework for a mobile OLAP system

Nachida

Boussaïd²,

Nader

2015

IJDSS

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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.Keywords: OLAP; contextual recommender system; data-mining; K2; OLAM; CBR; knowledge-based system; decision support systems.Reference to this paper should be made as follows: Rezoug, N., Boussaid, O. and Nader, F. (2015) This paper is a revised and expanded version of a paper entitled 'A contextual personalized recommender system for mobile OLAP' presented at the Information Technology and E-service (ICITes), Sousse, Tunis, 24-26 March 2012.

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