Ladjel Bellatreche

Ladjel Bellatreche received his PhD in computer science from the Clermont Ferrand University (France, 2000). He is an Assistant Professor in Computer Science at Poitiers University, France since 2002. Before joining Poitiers University, he has been a visiting researcher at Hong Kong University of Science and Technology (HKUST) from 1997 to 1999 and also has been a visiting researcher in the Computer Science Department at Purdue University, USA during the summer of 2001. He has worked extensively in the areas: heterogeneous data integration using formal ontologies, distributed databases, data warehousing, and data mining. He has published more than 75 research papers in these areas in leading international journal and conferences. Ladjel has been associated with many conferences and journals as program committee members.

Publications

Effectively and Efficiently Designing and Querying Parallel Relational Data Warehouses on Heterogeneous Database Clusters: The F&A Approach
Ladjel Bellatreche, Alfredo Cuzzocrea, Soumia Benkrid. © 2012. 35 pages.
In this paper, a comprehensive methodology for designing and querying Parallel Rational Data Warehouses (PRDW) over database clusters, called Fragmentation & Allocation (F&A) is...
Primary and Referential Horizontal Partitioning Selection Problems: Concepts, Algorithms and Advisor Tool
Ladjel Bellatreche, Kamel Boukhalfa, Pascal Richard. © 2011. 29 pages.
Horizontal partitioning has evolved significantly in recent years and widely advocated by the academic and industrial communities. Horizontal Partitioning affects positively...
Data Warehousing Design and Advanced Engineering Applications: Methods for Complex Construction
Ladjel Bellatreche. © 2010. 336 pages.
Data warehousing and online analysis technologies have shown their effectiveness in managing and analyzing a large amount of disparate data, attracting much attention from...
Bitmap Join Indexes vs. Data Partitioning
Ladjel Bellatreche. © 2009. 9 pages.
Scientific databases and data warehouses store large amounts of data ith several tables and attributes. For instance, the Sloan Digital Sky Survey (SDSS) astronomical database...
Bitmap Join Indexes vs. Data Partitioning
Ladjel Bellatreche. © 2009. 7 pages.
Scientific databases and data warehouses store large amounts of data ith several tables and attributes. For instance, the Sloan Digital Sky Survey (SDSS) astronomical database...
A Genetic Algorithm for Selecting Horizontal Fragments
Ladjel Bellatreche. © 2009. 6 pages.
Decision support applications require complex queries, e.g., multi way joins defining on huge warehouses usually modelled using star schemas, i.e., a fact table and a set of data...
Physical Data Warehousing Design
Ladjel Bellatreche, Mukesh Mohania. © 2009. 6 pages.
Recently, organizations have increasingly emphasized applications in which current and historical data are analyzed and explored comprehensively, identifying useful trends and...
Horizontal Data Partitioning: Past, Present and Future
Ladjel Bellatreche. © 2009. 9 pages.
Horizontal data partitioning is the process of splitting access objects into set of disjoint rows. It was first introduced in the end of 70’s and beginning of the 80’s (Ceri et...
SOM-Based Clustering of Textual Documents Using WordNet
Abdelmalek Amine, Zakaria Elberrichi, Michel Simonet, Ladjel Bellatreche, Mimoun Malki. © 2009. 12 pages.
The classification of textual documents has been the subject of many studies. Technologies like the Web and numerical libraries facilitated the exponential growth of available...
Referential Horizontal Partitioning Selection Problem in Data Warehouses: Hardness Study and Selection Algorithms
Ladjel Bellatreche, Kamel Boukhalfa, Pascal Richard, Komla Yamavo Woameno. © 2009. 23 pages.
Horizontal Partitioning has been largely adopted by the database community, where it took a significant part in the physical design process. Actually, it is supported by most...
Physical Data Warehousing Design
Ladjel Bellatreche, Mukesh Mohania. © 2005. 6 pages.
Recently, organizations have increasingly emphasized applications in which current and historical data are analyzed and explored comprehensively, identifying useful trends and...