J. Darmont

Publications
Influence

Automatic Selection of Bitmap Join Indexes in Data Warehouses

Kamel Aouiche, J. Darmont, Omar Boussaïd, F. Bentayeb
Computer Science
DaWaK
22 August 2005

The queries defined on data warehouses are complex and use several join operations that induce an expensive computational cost. Expand

Clustering-Based Materialized View Selection in Data Warehouses

Kamel Aouiche, P. Jouve, J. Darmont
Computer Science
ADBIS
3 September 2006

In this paper, we propose a framework for materialized view selection that exploits a data mining technique (clustering), in order to determine clusters of similar queries. Expand

Fusion Cubes: Towards Self-Service Business Intelligence

A. Abelló, J. Darmont, +8 authors G. Vossen
Computer Science
Int. J. Data Warehous. Min.
1 April 2013

Self-service business intelligence is about enabling non-expert users to make well-informed decisions by enriching the decision process with situational data, i.e., data that have a narrow focus on a specific business problem and, typically, a short lifespan for a small group of users. Expand

Data mining-based materialized view and index selection in data warehouses

Kamel Aouiche, J. Darmont
Computer Science
Journal of Intelligent Information Systems
10 July 2007

We couple materialized view and index selection to take view–index interactions into account and achieve efficient storage space sharing. Expand

Business intelligence for small and middle-sized entreprises

Oksana Grabova, J. Darmont, Jean-Hugues Chauchat, I. Zolotaryova
Computer Science
SGMD
6 December 2010

Data warehouses are the core of decision support systems, which nowadays are used by all kind of enterprises in the entire world. Although many studies have been conducted on the need of decision… Expand

OCB: A Generic Benchmark to Evaluate the Performances of Object-Oriented Database Systems

J. Darmont, Bertrand Petit, M. Schneider
Computer Science
EDBT
23 March 1998

We present in this paper a generic object-oriented benchmark (the Object Clustering Benchmark) that has been designed to evaluate the performances of clustering policies inobject-oriented databases. Expand

VOODB: A Generic Discrete-Event Random Simulation Model To Evaluate the Performances of OODBs

J. Darmont, M. Schneider
Computer Science
VLDB
7 September 1999

We propose a generic discrete-event random simulation model, called VOODB, in order to evaluate the performance of OODBs in general, and the performances of optimization methods like clustering in particular. Expand

Processing And Managing Complex Data for Decision Support

J. Darmont, O. Boussaid
Computer Science
1 April 2006

A Sample of Contents: Goal-Oriented Requirement Engineering for XML Document Warehouses Building an Active Content Warehouse Text Warehousing: Present and Future On the Usage of Structural Distance… Expand

Fragmenting very large XML data warehouses via K-means clustering algorithm

A. Cuzzocrea, J. Darmont, H. Mahboubi
Computer Science
Int. J. Bus. Intell. Data Min.
1 November 2009

We propose the use of the K-means clustering algorithm for effectively and efficiently supporting the fragmentation of very large XML data warehouses. Expand

Cost models for view materialization in the cloud

Thi-Van-Anh Nguyen, S. Bimonte, Laurent d'Orazio, J. Darmont
Computer Science
EDBT-ICDT '12
30 March 2012

We define new cost models that fit into the pay-as-you-go paradigm of cloud computing. Expand

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