Mohamed Rouane Hacene, Postdoc.
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Ancien(ne) étudiant(e) -
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Résumé - Lien
Ontologies are designed to evolve and this is typically done through sequences of a local modifications in the ontological structure, a.k.a. refactorings. Yet the more complex the structure the less obvious the full impact of such a refactoring. Thus, after a protracted period of maintenance, the overall quality of an ontology may substantially deteriorate. As a remedy, an ontology restructuring task would be performed that cleans its structure and enhances the ontology with new and previously missing entities. We investigate an approach for ontology restructuring based on relational concept analysis (RCA) that allows for a thorough reshuffling of the ontology. Here we present a platform for ontology maintenance, INUKHUK, and illustrate its main workflow dedicated to restructuring. We also report on a preliminary validating study involving several small-to-medium size ontologies.
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Zeina Azmeh, Marianne Huchard, Amedeo Napoli, Mohamed Rouane Hacene et Petko Valtchev, "Lessons learned in querying relational concept lattices.," in In Proc. of the 8th Intl. Conf. on Concept Lattices and Their Applications (CLA'11), Nancy, France, 2011. Mohamed Rouane Hacene, Schahrazed Fennouh, Roger Nkambou et Petko Valtchev, "Refactoring of Ontologies: Improving the Design of Ontological Models with Concept Analysis," in 22nd IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2010, Arras, France, 27-29 October 2010 - Volume, 2010, pp. 167--172. Mohamed Rouane Hacene, Schahrazed Fennouh, Roger Nkambou et Petko Valtchev, "Refactoring of ontologies: Improving the design of ontological models with concept analysis.," in Proc. of the 21st IEEE Intl. Conf. on Tools with Artif. Intell. (ICTAI'10), Arras, France, 2010, pp. 167-172. Mohamed Rouane Hacene, Marianne Huchard, Amedeo Napoli et Petko Valtchev, "Using formal concept analysis for discovering knowledge patterns," in Proc. of the 7th Intl. Conf. on Concept Lattices and Their Applications (CLA'10), 2010, pp. 223-234. Mohamed Rouane Hacene, Yannick Toussaint et Petko Valtchev, "Mining Safety Signals in Spontaneous Reports Database Using Concept Analysis," in Artificial Intelligence in Medicine, 12th Conference on Artificial Intelligence in Medicine, AIME 2009, Verona, Italy, July 18-2, 2009, pp. 285--294. Mohamed Rouane Hacene, Toussaint, Y., Petko Valtchev et & others, "Mining Safety Signals in Spontaneous Report Database using Concept Analysis," 12th Conference on Artificial Intelligence in Medicine-AIME 2009, 2009. Mohamed Rouane Hacene, M. Huchard, A. Napoli et Petko Valtchev, "Extraction de connaissances à partir de données relationnelles avec l'analyse formelle de concepts," in 16ème Congrès Francophone de Reconnaissance des Formes et d'Intelligence Artificielle (RFIA'08), Amiens, France, 2008. Mohamed Rouane Hacene, A. Napoli, Petko Valtchev, Y. Toussaint et R. Bendaoud, "Ontology Learning: Mining Transversal Relations from Text using Formal Concept Analysis," in Proceedings of the 3rd Montreal Conference on eTechnologies (MCETECH’08), Montréal, Canada, 2008, pp. 154-163. Mohamed Rouane Hacene, Hucahr, M., Napoli, A. et Petko Valtchev, "A proposal for combining formal concept analysis and description logics for mining relational data," Formal Concept Analysis, pp. 51-65, 2007. Mohamed Rouane Hacene, Dao, M., Hucahr, M. et Petko Valtchev, "Analyse formelle de données relationnelles pour la réingénierie des modèles UML," in LMO'07 : Langages et Modèles à Objets (2007), 2007, pp. 151-166. Mohamed Rouane Hacene, M. Huchard, A. Napoli et Petko Valtchev, "Extraction de concepts et de relations en analyse relationelle de concepts (ARC)," in Actes des XIVièmes rencontres de la Société Francophone de Classification, Paris, France, 2007, pp. 169-173. M. Huchard, Mohamed Rouane Hacene, Cyrille Roumé et Petko Valtchev, "Relational Concept Discovery in Structured Datasets," Annals of Mathematics and Artifficial Intelligence, vol. 49(1-4), pp. 39-76, 2007. Mohamed Rouane Hacene, M. Dao, M. Huchard et Petko Valtchev, "Aspects de la réingénierie des modèles UML par analyse de données relationnelles," Ingénierie des Systèmes d'Information, vol. 12(5), pp. 39-68, 2007. M. Huchard, A. Napoli, Mohamed Rouane Hacene et Petko Valtchev, "Mining description logics concept with concept lattices," in Selected Contributions in Data Analysis and Classification, P. Brito, P. Bertrand, G. Cucumel, F. De Carvalho ed.,: Springer Verlag, 2007, pp. . Dao, M., Hucahrd, M., Mohamed Rouane Hacene, Roume. C. et Petko Valtchev, "Towards practical tools for mining abstractions in UML models," in ICEIS, 2006, pp. 276-283. Nehmé, K., Petko Valtchev, Mohamed Rouane Hacene et Robert Godin, "On computing the minimal generator family for concept lattices and icebergs," Formal Concept Analysis, 2005. Dao, M., Hucahrd, M, Mohamed Rouane Hacene, Roume, C., Petko Valtchev et & others, "Mettez un Treillis dans votre Modèle! Réflexions sur la Place et les Moyens de la Classification dans l'Ingénierie des Modèles," in IDM'05: Premières Journées sur l'Ingénierie Dirigée par les Modèles, 2005. Mohamed Rouane Hacene, Petko Valtchev, Sahraoui, H, Huchard, M. et & others, "Merging conceptual hierarchies using concept lattices," in MASPEGHI'04: 3rd Workshop on Managing SPEcialization/Generalization Hierarchies, Oslo, Norway, 2004. Mohamed Rouane Hacene, Nehme, K, Petko Valtchev et Robert Godin, "On-line maintenance of iceberg concept lattices," in Contributions to the 12th ICCS, 2004. Dao, M., Huchard, M, Mohamed Rouane Hacene, Roume, C. et Petko Valtchev, "Improving generalization level in UML models iterative cross generalization in practice," Conceptual Structures at Work, pp. 238-238, 2004. Petko Valtchev, Mohamed Rouane Hacene et Rokia Missaoui, "A Generic Scheme for the Design of Efficient On-Line Algorithms for Lattices," in Conceptual Structures for Knowledge Creation and Communication, 11th International Conference on Conceptual Structures, ICCS 200, 2003, pp. 282--295. Petko Valtchev, Rokia Missaoui, Mohamed Rouane Hacene et Robert Godin, "Incremental Maintenance of Association Rule Bases.," in Acte de l'atelier sur les Discrete Mathematics and Data Mining, en association avec la 3rd SIAM Conference on Data Mining, San Francisco (CA), USA, 2003. Petko Valtchev, Mohamed Rouane Hacene et Rokia Missaoui, "A Generic Scheme for the Design of Efficient Online Algorithms for Concept Lattices," in the 11th International Conference on Conceptual Structures (ICCS’2003), Dresden, Allemagne, 2003.
doi: 10.1109/ICTAI.2010.97 ISBN: 978-1-4244-8817-9
Résumé - Télécharger - Lien
Résumé - Télécharger - Lien
It is now widely accepted that in order to optimize both their usage and their design and maintenance ontologies should comply to design quality criteria, e.g., absence of redundancies and appropriate level of abstraction. Yet given the variety and scope of activities comprised in the life-cycle of an ontological model (OM), such as adapting, splitting, populating, this quality is easily compromised, especially with ontologies of larger size and/or resulting from the merge of smaller ones. Conversely, restoring it through refactoring, i.e., restructuring of the ontology to improve defects, is knowingly a challenging task as relocating an ontology element can adversely affect its neighbors. We investigate here a holistic refactoring approach that, given an ontology, amounts to presenting its designer with a list of the most plausible abstract entities missing in it. The core of the approach is a recently devised concept analysis method, called 'relational', that allows deeper refactoring by feeding into the process various ontological relations, e.g., concept-to-property incidences. The focus here is put on the NLP-aspects of the refactoring, while we also provide some preliminary results from a series of validating experiments.
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Association rule mining from transaction databases (TDB) is a classical data mining task, whereby the most computationally intensive step is the detection of frequently occurring patterns, called frequent itemsets ( FIs), from which the rules are further extracted. The number of FIs may be potentially large, leading to an even greater number of rules. Approaches based on closure operators, Galois conections and Galois (concept) lattices have been proposed in an attempt to reduce the size of the resulting rule set. Thus, the search for frequent patterns has been limited to closed itemsets, while looking for a representative and reduced set of association rules, called a basis, which nevertheless conveys all the relevant information. In thess approaches, the minimal generators of a closed itemset play a key role for the itemset/rule construction. In our paper, we present a straightforward method for the maintenance of an association rule basis when a new transaction is added to the TDB. To that end, we utilize results on the incremental update of lattices and extend them with new properties to form a complete framework for association rule base maintenance. In particular, we define a simple and efficient method for on-line computation of the generators for closed itemsets and show how its output is used in the update of the rule basis.