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28
Knowledge provenance: An approach to modeling and maintaining the evolution and validity of knowledge
, 2003
"... www.eil.utoronto.ca ..."
Towards peer-to-peer semantic web: A distributed environment for sharing semantic knowledge on the web
- Proc of the International World Wide Web Conference,WWW
, 2002
"... Abstract. The real value of Semantic Web vision can be demonstrated if people and applications can create and discover new and interesting knowledge and share this knowledge in a transparent manner similar to the way data is exchanged today. Therefore, we believe that Semantic Web will consist of a ..."
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Cited by 18 (2 self)
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Abstract. The real value of Semantic Web vision can be demonstrated if people and applications can create and discover new and interesting knowledge and share this knowledge in a transparent manner similar to the way data is exchanged today. Therefore, we believe that Semantic Web will consist of a distributed environment of shared and interoperable ontologies, which have emerged as common formalisms for knowledge representation. The users will need to discover new ontologies, which are not known to them before and use them to either annotate the content or to formulate their information requests. This requires an environment that supports creating, maintaining, and controlled sharing of ontologies. We believe that a Peer-to-Peer (P2P) infrastructure can enable such capabilities. We call our approach P2P Semantic Web (PSW) with capabilities to find relevant set of ontologies, facilitating reuse of existing ontologies to create additional ontologies, and advertising the resulting ontologies. We discuss an ontology driven search of concepts and services and exploration of inter-ontological relationships over a P2P infrastructure. The prototyping of this approach in the InfoQuilt system is also discussed. 1.
Ontology-based organizational memory for elearning
- Educational Technology & Society
, 2004
"... e-learning leads to evolutions in the way of designing a course. Diffused through the web, the course content cannot be the direct transcription of a face to face course content. A course can be seen as an organization in which different actors are involved. These actors produce documents, informati ..."
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Cited by 14 (3 self)
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e-learning leads to evolutions in the way of designing a course. Diffused through the web, the course content cannot be the direct transcription of a face to face course content. A course can be seen as an organization in which different actors are involved. These actors produce documents, information and knowledge that they often share. We present in this paper an ontology-based document-driven memory which is particularly adapted to an e-learning situation. The utility of a shared memory is reinforced in this kind of situation, because the interactions do not usually occur in the same place and in the same time. First we precise our conception of e-learning and we analyze actors needs. Then we present the main features of our learning organizational memory and we focus on the ontologies on which it is based. We consider two kinds of ontologies: the first one is generic and concerns the domain of training; the second one is related to the application domain and is specific to a particular training program. We present our approach for building these ontologies and we show how they can be merged. Finally we describe the learning memory and the prototype we realized for two course units proposed in our universities.
Semantic Management: advantages of using an ontology-based management information meta-model
- Proceedings of the HP Openview University Association Ninth Plenary Workshop (HP-OVUA'2002), distributed videoconference
, 2002
"... The multiplicity of Network Management models (SNMP, CMIP, DMI, WBEM...) has raised in the last years the need of defining multiple mechanisms to allow the interoperability among all involved management domains. One basic component of such interoperability is the mapping between the information mode ..."
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Cited by 12 (0 self)
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The multiplicity of Network Management models (SNMP, CMIP, DMI, WBEM...) has raised in the last years the need of defining multiple mechanisms to allow the interoperability among all involved management domains. One basic component of such interoperability is the mapping between the information models that each domain specifies. Usually, these mappings have been carried out with syntactical translations that do not include the semantic aspects of the defined information. These translations could reach the semantic level by using ontologies: these ontologies widely used in Artificial Intelligence, exactly focus on the meaning of those concepts composing an information model.
Query processing using ontologies
- IN: PROCEEDINGS OF THE 17TH CONFERENCE ON ADVANCED INFORMATION SYSTEMS ENGINEERING (CAISE’05
, 2005
"... Recently, the database and AI research communities have paid increased attention to ontologies. The main motivating reason is that ontologies promise solutions for complex problems caused by the lack of a good understanding of the semantics of data in many cases. In particular, ontologies have exten ..."
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Cited by 7 (0 self)
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Recently, the database and AI research communities have paid increased attention to ontologies. The main motivating reason is that ontologies promise solutions for complex problems caused by the lack of a good understanding of the semantics of data in many cases. In particular, ontologies have extensively been used to overcome the interoperability problem during the integration of heterogeneous information sources. Moreover, many efforts have been put into developing ontology based techniques for improving the query answering process in database and information systems. In this paper, we present a new approach for query processing within single (object) relational databases using ontology knowledge. Our goal is to process database queries in a semantically more meaningful way. In fact, our approach shows how an ontology can be effectively exploited to rewrite a user query into another one such that the new query provides more meaningful results satisfying the intention of the user. To this end, we develop a set of transformation rules which rely on semantic information extracted from the ontology associated with the database. In addition, we specify the necessary mappings between an ontology and its underlying database w.r.t. our framework.
2002b). “A framework for technology convergence in learning and working
- Educational Technology and Society, Journal of International Forum of Educational Technology & Society and IEEE Learning Technology Task Force, Vol 5(2
"... Information technology is arguably an important tool for knowledge management, facilitating learning in a business context. However, the current use of information technology in this area often fails to take into account the multifaceted and dynamic nature of knowledge creation, knowledge transfer a ..."
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Cited by 6 (3 self)
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Information technology is arguably an important tool for knowledge management, facilitating learning in a business context. However, the current use of information technology in this area often fails to take into account the multifaceted and dynamic nature of knowledge creation, knowledge transfer and learning. In order to address this issue, the paper proposes a dynamic learning model that is based on three complementary dimensions: knowledge management, technology-supported learning pedagogy and application integration. We argue that this multidimensional model illustrates how technology-supported learning can work as a value-added process that supports the different needs of learners and businesses.
Knowledge Source Network Configuration Approach to Knowledge Logistics
- Taylor & Francis Group
, 2003
"... Abstract—Today an intensive knowledge exchange between participants of the global information environment is required. Along with a large number of distributed knowledge sources representing knowledge in various formats this leads to appearance of a new direction in knowledge management called knowl ..."
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Cited by 5 (4 self)
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Abstract—Today an intensive knowledge exchange between participants of the global information environment is required. Along with a large number of distributed knowledge sources representing knowledge in various formats this leads to appearance of a new direction in knowledge management called knowledge logistics. The paper describes Knowledge Source Network configuration approach (KSNet-approach) to knowledge logistics through knowledge fusion. It is based on such technologies as ontology management and intelligent agents. The most important ideas of the proposed KSNet-approach were implemented and verified via developed software prototype of the system "KSNet". Index Terms—Cooperative systems, distributed information systems, knowledge based systems, knowledge representation, intelligent systems, logistics R I.
EER-CONCEPTOOL: a “Reasonable” Environment for Schema and Ontology Sharing
- In Proc. of the 14th IEEE International Conference on Tools with Artificial Intelligence (ICTAI2002), IEEE Computer
, 2002
"... We propose a system which supports knowledge sharing through the articulation of the overlapping components in two or more schemas or ontologies. EER-CONCEPTOOL uses Description Logics (DLs) to formalise and capture some relevant features of knowledge described using an Enhanced Entity-Relationship ..."
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Cited by 5 (2 self)
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We propose a system which supports knowledge sharing through the articulation of the overlapping components in two or more schemas or ontologies. EER-CONCEPTOOL uses Description Logics (DLs) to formalise and capture some relevant features of knowledge described using an Enhanced Entity-Relationship (EER) model. We describe how DL-based reasoning can provide a relevant part of the semiautomated deductive support needed to specify the articulation (i.e. the shared content) of two EER knowledge bases. We also show how a more effective level of support can be provided by the EER-CONCEPTOOL architecture, which combines DL-based deductions with lexical analysis and heuristic inferences. We illustrate the approach to knowledge articulation in our system by way of an example. 1.
Ontology-based Support for Variability Management in Product and Service Families
, 2003
"... Product/service family engineering, which encourages the development of a common product platform, plays a key role in facilitating large-scale and planned reuse in the development of customized products. In product family designs, managing points of variability is critical to achieve product variet ..."
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Cited by 4 (0 self)
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Product/service family engineering, which encourages the development of a common product platform, plays a key role in facilitating large-scale and planned reuse in the development of customized products. In product family designs, managing points of variability is critical to achieve product variety. Variation points are points at which one among the several possible variations of a feature of a system can be selected to achieve different configurations of a product. We are developing an ontology that catalogues the different concepts associated with variability. This ontology is used to define the elements characterizing the knowledge elements necessary for managing variability in product/service families. We have also developed a knowledge management system integrated with an ontology development tool to facilitate knowledge capture and retrieval for variability management.
Knowledge Management for Computational Problem Solving
- Journal of Universal Computer Science
"... Algorithmic research is an established knowledge engineering process that has allowed researchers to identify new or significant problems, to better understand existing approaches and experimental results, and to obtain new, effective and efficient solutions. While algorithmic researchers regularly ..."
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Cited by 4 (1 self)
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Algorithmic research is an established knowledge engineering process that has allowed researchers to identify new or significant problems, to better understand existing approaches and experimental results, and to obtain new, effective and efficient solutions. While algorithmic researchers regularly contribute to this knowledge base by proposing new problems and novel solutions, the processes currently used to share this knowledge are inefficient, resulting in unproductive overhead. Most of these publication-centred processes lack explicit high-level knowledge structures to support efficient knowledge management. The authors describe a problem-centred collaborative knowledge management architecture associated with Computational Problem Solving (CPS). Specifically we articulate the structure and flow of such knowledge by making in-depth analysis of the needs of algorithmic researchers, and then extract the ontology. We also propose a knowledge flow measurement methodology to provide human-centred evaluations of research activities within the knowledge structure. This measurement enables us to highlight active research topics and to identify influential researchers. The collaborative knowledge management architecture was realized by implementing an Open Computational Problem Solving (OpenCPS) Knowledge Portal, which is an open-source project accessible at http://www.opencps.org.
