Mining Partially-Ordered Sequential Rules Common to Multiple Sequences

© 2015 IEEE. Sequential rule mining is an important data mining problem with multiple applications. An important limitation of algorithms for mining sequential rules common to multiple sequences is that rules are very specific and therefore many similar rules may represent the same situation. This can cause three major problems: (1) similar rules can be rated quite differently, (2) rules may not be found because they are individually considered uninteresting, and (3) rules that are too specific are less likely to be used for making predictions. To address these issues, we explore the idea of mining "partially-ordered sequential rules" (POSR), a more general form of sequential rules such that items in the antecedent and the consequent of each rule are unordered. To mine POSR, we propose the RuleGrowth algorithm, which is efficient and easily extendable. In particular, we present an extension (TRuleGrowth) that accepts a sliding-window constraint to find rules occurring within a maximum amount of time. A performance study with four real-life datasets show that RuleGrowth and TRuleGrowth have excellent performance and scalability compared to baseline algorithms and that the number of rules discovered can be several orders of magnitude smaller when the sliding-window constraint is applied. Furthermore, we also report results from a real application showing that POSR can provide a much higher prediction accuracy than regular sequential rules for sequence prediction

Grid-based virtual clinic for medical diagnosis tutoring

Les technologies émergeantes basées sur la grille sont de plus en plus adoptées pour rehausser l\'éducation et fournir de meilleurs services pour l\'apprentissage. Cela se caractérise de part le monde par le développement de systèmes tutoriels largement distribués. Les apprenants, indépendamment de leurs systèmes informatiques peuvent accéder à des connaissances partagées sur des sites répartis. Généralement, les outils d\'enseignement existants sont basés sur le transfert d\'information plutôt que sur une approche synergique centrée sur la construction des connaissances. Dans cet article, nous proposons une clinique virtuelle basée sur la grille comme cadre de formation au diagnostic médical. La réalisation visée est un outil collaboratif d\'enseignement pour les médecins du terrain et les étudiants en médecine au sein d\'une organisation virtuelle.The emerging grid-based technologies are increasingly adopted to enhance education and provide better learning services. This is characterized all over the world, by the development of large scale tutoring systems. Learners, regardless of their different computer systems have access to knowledge across distributed site. Commonly, classical teaching tools are based on information transfer approach rather than a synergic approach focused on knowledge construction. In this paper, we propose a grid-based virtual clinic for medical diagnosis tutoring. The aimed realization is a convenient collaborative training tool for field doctors and medical students within a virtual organization. Keywords: Grid, Système tutoriel, Clinique virtuelle, Diagnostic médical; Grid, Tutoring system, Virtual clinic, Medical diagnosis. Journal des Sciences Pour l\'Ingénieur. Vol. 7 2006: pp. 72-7

Building Domain Ontologies from Text for Educational Purposes

Abstract. In this paper, we present a (semi) automatic framework that aims to produce a domain concept map (DCM) from text and to derive a domain ontology from this concept map. This methodology targets particularly the educational field because of the need of such structures (Ontologies and CM) within the e-Learning and AIED communities to sustain the production of e-Learning resources tailored to learner’s needs. This paper details the steps that transform textual resources (and particularly textual learning objects) into a domain concept map and explains how this abstract structure is transformed into a more formal domain ontology. The paper also shows how these structures make it possible to bridge the gap between e-learning standard learning object

CARI'96 : actes du 3ème colloque africain sur la recherche en informatique = CARI'96 : proceedings of the 3rd African conference on research in computer science

L'intégration d'un client "World Wide Web" (WWW) dans un processus d'enseignement-apprentissage nécessite d'étudier la gestion des ressources pédagogiques par le client et la communication avec les autres modules du système d'enseignement. Nous présentons dans ce papier, une architecture de système tutoriel intelligent (STI) utilisant un client WWW comme interface de l'apprenant. Cette interface permet de supporter le déroulement de toute ressource pédagogique faisant partie d'une matière à enseigner par un STI. (Résumé d'auteur