Knowledge Representation and Retrieval in Design Project Memory
Commenced in January 2007
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Edition: International
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Knowledge Representation and Retrieval in Design Project Memory

Authors: Smain M. Bekhti, Nada T. Matta

Abstract:

Knowledge sharing in general and the contextual access to knowledge in particular, still represent a key challenge in the knowledge management framework. Researchers on semantic web and human machine interface study techniques to enhance this access. For instance, in semantic web, the information retrieval is based on domain ontology. In human machine interface, keeping track of user's activity provides some elements of the context that can guide the access to information. We suggest an approach based on these two key guidelines, whilst avoiding some of their weaknesses. The approach permits a representation of both the context and the design rationale of a project for an efficient access to knowledge. In fact, the method consists of an information retrieval environment that, in the one hand, can infer knowledge, modeled as a semantic network, and on the other hand, is based on the context and the objectives of a specific activity (the design). The environment we defined can also be used to gather similar project elements in order to build classifications of tasks, problems, arguments, etc. produced in a company. These classifications can show the evolution of design strategies in the company.

Keywords: Project Memory, Knowledge re-use, Design rationale, Knowledge representation.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1333140

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[1] Berners-Lee, T. & Hendler, J. & Lassila, O. the Semantic Web, In: Scien-tific American. 2001
[2] Jing, Y. & Taylor, N. & Brown, K., An intelligent Inference Approach to user Interaction Modelling in a generic Agent Based Interface System, In pro-ceedings of ECAI2002 (European Conference on Artificial Intelligence), July, Lyon. 2002
[3] Bekhti, S., & Matta, N. Project memory: An approach of modelling and reusing the context and the de design rationale, Proceedings of IJCAI'03 (Interna-tional joint of conferences of Artificial Intelligence) Workshop on knowledge management and organisational memory, Accapulco. 2003
[4] Corby, O. & Faron-Zucker, C., Corese: A Corporate Semantic Web Engine, Workshop on Real World RDF and Semantic Web Applications 11th Inter-national World Wide Web Conference, Hawaii. 2002
[5] Dieng-Kuntz-Kuntz, R. & Corby; O. & Gandon, F. & Giboin; A. & Golebiowska, J. & Matta; N. & Ribière, M. Méthodes et outils pour la gestion des con-naissances. 2eme edition. Dunod éditeur. 2001
[6] Van Heijst; G. & Schreiber, A. & Wielinga, B. Using Explicit Ontologies in KBS Development. International Journal of Human Computer Studies, Vol. 46. 1997
[7] Matta, N. Conflict Management in Concurrent Engineering: Modelling Guides. Computational Conflicts: Conflict Modeling for Distributed Intelligent Systems, with Contributions by Numerous Experts. Springer. 2000
[8] Karsenty, L. An empirical evaluation of design rationale documents. In: Proceedings of the Conference on Human Factors in Computing Systems. Van-couver. 1996
[9] Buckingham, S. Representing Hard-to-Formalise, Contextualised, Multid-isciplinary, Organisational Knowledge. Proceedings of AAI Spring Symposium on Artificial Intelligence in Knowledge Management, P.9-16. 1997
[10] Klein, M. Capturing Design Rationale in Concurrent Engineering Teams, IEEE, Computer Support for Concurrent Engineering. 1993
[11] Matta, N. & Ribière, M. & Corby, O. & Lewkowicz, M. & Zacklad, M. Project Memory in Design, Industrial Knowledge Management - A Micro Level Approach. SPRINGER-VERLAG: RAJKUMAR ROY, 2000.
[12] Brown, D. C. & Berker, I.. Modeling Conflicts Between Agents in a Design Context, Computational conflicts, Conflicts Modeling for Distributed Intelligent System, 144-164, Springer. 2000
[13] Martin, M. Links between Electronic Documents and a Knowledge Base of Conceptual Graphs. In proceedings of the International Conference on Concep-tual Structures of ICCS. 1995
[14] Chein M. & Mugnier M.L. Specialization: Where do the difficulties occur? In Proceeding of the seventh Annual Workshop on Conceptual Structures, Las cruces, New Mexico. 1992
[15] Sowa, L. Conceptual Structures: Information Processing in Mind and Ma-chine. Addison-Wesley, Reading, MA. 1984
[16] RDF Vocabulary Description Language 1.0: RDF Schema W3C Recommenda-tion, February 10, 2004 Dan Brickley, R.V. Guha, eds. 2004
[17] Corby, O. & Dieng, R. & Faron-Zucker C. Querying the Semantic Web with Corese Search Engine, Prestigious Applications of Intelligent Systems PAIS, ECAI, Valencia. 2000