@conference { ISI:000373729000021,
	title = {Ontology Learning from Relational Database: How to Label the Relationships Between Concepts?},
	booktitle = {BEYOND DATABASES, ARCHITECTURES AND STRUCTURES, BDAS 2015},
	series = {Communications in Computer and Information Science},
	volume = {521},
	year = {2015},
	note = {11th International Conference on Beyond Databases, Architectures and Structures (BDAS), Ustron, POLAND, MAY 26-29, 2015},
	pages = {235-244},
	publisher = {IEEE Poland Sect; Silesian Univ Technol, Inst Informat},
	organization = {IEEE Poland Sect; Silesian Univ Technol, Inst Informat},
	abstract = {Developing ontology for modeling the universe of a Relational Database (RDB) is a key success for many RDB related domains, including semantic-query of RDB, Linked Data and semantic interoperability of information systems. However, the manual development of ontology is a tedious task, error-prone and requires much time. The research field of ontology learning aims to provide (semi-) automatic approaches for building ontology. However, one big challenge in the automatic transformation, is how to label the relationships between concepts. This challenge depends heavily on the correct extraction of the relationship types. In fact, the RDB model does not store the meaning of relationships between entities, it only indicates the existence of a link between them. This paper suggests a solution consisting of a meta-model for the semantic enrichment of the RDB model and of a classification of relationships. A case study shows the effectiveness of our approach.},
	isbn = {978-3-319-18422-7; 978-3-319-18421-0},
	issn = {1865-0929},
	doi = {10.1007/978-3-319-18422-7\_21},
	author = {El Idrissi, Bouchra and Baina, Salah and Baina, Karim},
	editor = {Kozielski, S and Mrozek, D and Kasprowski, P and MalysiakMrozek, B and Kostrzewa, D}
}
@conference { ISI:000345780300021,
	title = {Automatic Generation of Ontology from Data Models: A Practical Evaluation of Existing Approaches},
	booktitle = {2013 IEEE SEVENTH INTERNATIONAL CONFERENCE ON RESEARCH CHALLENGES IN INFORMATION SCIENCE (RCIS)},
	series = {International Conference on Research Challenges in Information Science},
	year = {2013},
	note = {7th IEEE International Conference on Research Challenges in Information Science (RCIS), Paris, FRANCE, MAY 29-31, 2013},
	publisher = {IEEE; Univ Paris 1; Ctr Rech \& Informatique; IEEE French Sect; Cyrius Consulting; IEEE French CS Joint Chapter},
	organization = {IEEE; Univ Paris 1; Ctr Rech \& Informatique; IEEE French Sect; Cyrius Consulting; IEEE French CS Joint Chapter},
	abstract = {Nowadays, ontology as a knowledge sharing approach plays an important role in semantic interoperability of enterprise applications (EAs). However, the manual process of ontology construction requires deep understanding of the domain. This approach is difficult, expensive and time-consuming. To overcome the knowledge acquisition bottleneck, ontology learning field aims to provide automatic and semi-automatic approaches for ontology generation. Several approaches have been emerged for this purpose. In this paper, we present a practical study of methods that take data models as input to the learning process. The main contributions of this work are: (i) the evaluation of the availability of existing approaches for (semi-)automatic generation of ontology from data models; (ii) the evaluation of tools according to their operability; and (iii) the evaluation of the resulting ontologies to assess their quality in supporting semantic interoperability. Our goal through this study is to find a response to the question: Is there a tool that extracts (semi-) automatically an application ontology from data models, intended for use in semantic interoperability?.},
	isbn = {978-1-4673-2912-5},
	issn = {2151-1349},
	author = {El Idrissi, Bouchra and Baina, Salah and Baina, Karim},
	editor = {Wieringa, R and Nurcan, S and Rolland, C and Cavarero, JL}
}
@conference { ISI:000350287800030,
	title = {Ontology Learning from Data Models: Advance and the Requirement for a Database Preparation and Enrichment Process},
	booktitle = {2013 3RD INTERNATIONAL SYMPOSIUM ISKO-MAGHREB},
	year = {2013},
	note = {ISKO-Maghreb 3rd International Symposium, Marrakech, MOROCCO, NOV 08-09, 2013},
	publisher = {ISKO},
	organization = {ISKO},
	abstract = {Ontology learning field provides automatic and semi-automatic approaches for ontology generation. This process aims to overcome the manual knowledge acquisition process that is difficult, expensive and time-consuming. Several approaches have been emerged for this purpose. However, they are not practical on real-world databases and they are far from capturing all application semantics. This paper gives, first, an overview of the ontology learning process and the peculiarities of relational models. Then, it discusses the advance in this filed according to a developed framework before presenting two main lacks: the requirement of a database preparation process and an enrichment process.},
	isbn = {978-1-4799-3392-1},
	author = {El Idrissi, Bouchra and Baina, Salah and Baina, Karim}
}
