Contextual-Ontologies for an AutoE-Learning Process
TL;DR: A method which defines laws to relate automatically relevant parts of different ontologies, based on a mathematical model "Information Flow", is proposed to coordinate these ontologies in order to expand the reuse, the search, the share of learning resources.
Abstract: According to Brezillon, context is not directly involved in solving a problem, but forced his resolution In educational community, knowledge is transmitted from tutor to learners However, two main issues are occurred On one hand, Learner is facing resource bank and s/he has to seek the appropriate information from the relevant resource To solve this problem, it is required to help learner by providing the context of resources in a pertinent organization Ontologies represent the essential technology for the organization of eLearning resources On the other hand, a massive amount of ontologies have spread among eLearning Systems Our objective is to coordinate these ontologies in order to expand the reuse, the search, the share of learning resources For that aim, we propose a method which defines laws to relate automatically relevant parts of different ontologies, based on a mathematical model "Information Flow"
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Proceedings Article•
06 Nov 2000
TL;DR: In this paper, the authors present an approach to learning and teaching support in respect of information handling and knowledge management within web-based learning environments, where learners perform open learning tasks.
Abstract: This paper addresses an innovative approach to learning and teaching support in respect of information handling and knowledge management within web-based learning environments, where learners perform open learning tasks. The approach involves integrated domain-oriented informational support for both learners and instructors. It has three significant aspects: 1, building a domain ontology (represented as a concept map) and using it for defining course structures; 2, powerful visualisation and graphical navigation of the subject domain and the information search results; and 3, adaptation to the individual information needs and preferences of the learners. A system prototype called AIMS exemplifies the main ideas of this approach. It represents a task-based information and performance support system with an underlying agent-oriented architecture. Several pilot experiments are being performed within web-based courses in Dutch and Belgian universities to evaluate the system.
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TL;DR: This paper describes a mechanism for defining ontologies that are portable over representation systems, basing Ontolingua itself on an ontology of domain-independent, representational idioms.
12,962 citations
Book•
01 Jan 1997TL;DR: The authors, observing that information flow is possible only within a connected distribution system, provide a mathematically rigorous, philosophically sound foundation for a science of information.
Abstract: Information is a central topic in computer science, cognitive science, and philosophy. In spite of its importance in the "information age," there is no consensus on what information is, what makes it possible, and what it means for one medium to carry information about another. Drawing on ideas from mathematics, computer science, and philosophy, this book addresses the definition and place of information in society. The authors, observing that information flow is possible only within a connected distribution system, provide a mathematically rigorous, philosophically sound foundation for a science of information. They illustrate their theory by applying it to a wide range of phenomena, from file transfer to DNA, from quantum mechanics to speech act theory.
723 citations
TL;DR: In this article, the authors present a theory and method for automated ontology mapping based on channel theory, a mathematical theory of semantic information flow, which is applied to a large-scale scenario involving the mapping of several different ontologies of computer-science departments from various UK universities.
Abstract: In order to tackle the need of sharing knowledge within and across organisational boundaries, the last decade has seen researchers both in academia and industry advocating for the use of ontologies as a means for providing a shared understanding of common domains. But with the generalised use of large distributed environments such as the World Wide Web came the proliferation of many different ontologies, even for the same or similar domain, hence setting forth a new need of sharing–that of sharing ontologies. In addition, if visions such as the Semantic Web are ever going to become a reality, it will be necessary to provide as much automated support as possible to the task of mapping different ontologies. Although many efforts in ontology mapping have already been carried out, we have noticed that few of them are based on strong theoretical grounds and on principled methodologies. Furthermore, many of them are based only on syntactical criteria. In this paper we present a theory and method for automated ontology mapping based on channel theory, a mathematical theory of semantic information flow. We successfully applied our method to a large-scale scenario involving the mapping of several different ontologies of computer-science departments from various UK universities.
243 citations
01 Jan 1999
TL;DR: In this paper, the authors discuss the role of contexte in the developpement of systemes d'assistance intelligents, and propose a representation explicite du contexTE.
Abstract: Nous nous efforcons de montrer, dans l'optique du developpement de systemes d'assistance intelligents, que la cooperation est indissociable des explications et de l'acquisition incrementale de connaissances et que le contexte joue un role essentiel dans ces processus. Les explications sont une partie intrinseque de toute cooperation car elles permettent le partage de connaissances en etendant le contexte de la cooperation et donc, de renforcer cette cooperation. Inversement, en explicitant le contexte de la cooperation, il est possible de produire des explications plus pertinentes, ce qui a pour but de renforcer la cooperation. L'acquisition incrementale de connaissances permet au systeme de s'ameliorer au cours d'une resolution de probleme (les connaissances etant alors acquises dans leur contexte d'utilisation) et donc, au cours de toutes ses interactions ulterieures avec un utilisateur. L'acquisition incrementale de connaissances est importante dans la generation d'explications car le systeme doit pouvoir accepter des explications de l'utilisateur. Pour ces deux aspects de la cooperation, il est necessaire de trouver une representation explicite du contexte. Partant de notre experience dans le developpement de systemes, en particulier, dans le systeme SART d'aide a la resolution d'incidents sur une ligne de metro, nous illustrons notre conception du contexte dans les systemes d'assistance. A partir d'exemples, nous proposons quelques pistes pour definir le contexte. Nous montrons qu'il existe differents types de contexte et qu'il est plus judicieux de parler de connaissances contextuelles et de contexte proceduralise, le statut des differents types de connaissances evoluant au cours de la resolution d'un probleme. Cette explicitation du contexte rend la cooperation plus efficace, les echanges plus pertinents et donc moins nombreux.
211 citations