Knowledge Representation and Retrieval in Design Project Memory
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.
[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
[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
@article{"International Journal of Information, Control and Computer Sciences:56155", author = "Smain M. Bekhti and Nada T. Matta", title = "Knowledge Representation and Retrieval in Design Project Memory", 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.", volume = "3", number = "7", pages = "1765-7", }