Due to the increased complexity of engineering products and design process, concurrent engineering practices still face enormous challenges. Design teams often provide the knowledge involving multiple disciplines in natural language at conceptual design stage. As a result, conflicts often arise during communications. To increase the efficiency of design process, it is necessary to avoid interpretation conflicts. This article presents a system framework to resolve terminology conflicts. First, a semantic hierarchical structure of knowledge is proposed. Knowledge is decomposed into terms and predicates. Second, a fuzzy knowledge fusion framework is proposed to identify and resolve terminology conflicts. The conflict is resolved by unifying the usage of terminologies. By using the fuzzy linguistic computational model based on extension principle to measure the similarity of terms, the terminology conflict problem is converted into a linguistic decision-making problem. Finally, the methodology is applied to a piece of automotive electronics knowledge. The best term to describe electronic control unit is identified.
Klein, M. ( 1993). Supporting Conflict Management in Cooperative Design Teams, Journal of Group Decision Making and Negotiation, 2(9): 259-278.
2.
Pearlman, W. (1998). Towards a General System for Knowledge Fusion, A System for Knowledge Fusion, 25(7/8): 135-140.
3.
Klein, M. ( 1995). iDCSS Integrating Workflow, Conflict and Rationale-based Concurrent Engineering Coordination Technologies, Concurrent Engineering, 3(1): 21-27.
4.
Yassine, A. and Braha, D. ( 2003). Complex Concurrent Engineering and the Design Structure Matrix Method, Concurrent Engineering: Research and Applications , 11(3): 165-176.
5.
Wang, L.H. and Shen, W.M. ( 2002). Collaborative Conceptual Design: State of the Art and Future Trends, Computer-aided Design, 34: 981-996.
6.
Klein, M. ( 1991). Supporting Conflict Resolution in Cooperative Design Systems, IEEE Transactions on Systems, Man and Cybernetics, Special Issue on Distributed Artificial Intelligence, 21(6): 1379-1390.
7.
Matta, N. and Corby, O. ( 1996). Conflict Management in Concurrent Engineering: Modeling Guides, In: Muller, H.J. and Dieng, R. (eds), Computational Conflicts: Conflict Modeling for Distributed Intelligent Systems, pp. 125-143, New York: Springer.
8.
Klein, M. ( 2000). Towards a Systematic Repository of Knowledge about Managing Collaborative Design Conflicts, In: Proceedings of the Sixth International Conference on Artificial Intelligence in Design, Boston MA: Kluwer Academic Publishers, 26-29 June, pp. 129-146.
9.
Shastri, L. and Wendelken, C. ( 1999). Knowledge Fusion in the Large: Taking a Cue from the Brain, In: Proceedings of the 2nd International Conference on Information Fusion, Sunnyvale, USA, 6-8 July, pp. 1262-1269.
10.
Smirnov, A. , Pashkin, M., Chilov, N. and Levashova, T. (2002). Multi-agent Architecture for Knowledge Fusion from Distributed Sources, Lecture Notes in Artificial Intelligences, 2296: 293-302.
11.
Preece, A. and Hui, K. ( 2001). KRAFT: An Agent Architecture for Knowledge Fusion, International Journal of Cooperative Information Systems, 10(1-2): 171-195.
12.
Xie, N.F. , Cao, C.G. and Guo, H.Y. (2005). A Knowledge Fusion Model for Web Information, In: Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence, Compiegne, France, 19-22 September, pp. 67-72.
13.
Heffner, M. and Sharif, N. (2008). Knowledge Fusion for Technological Innovation in Organizations, Journal of Knowledge Management, 12(2): 79-93.
14.
Preece, A. and Hui, K. ( 2000). The KRAFT Architecture for Knowledge Fusion and Transformation , Knowledge Based Systems, 13(2-3): 113-120.
15.
Gray, W.A. and Preece, A. ( 1997). KRAFT: Knowledge Fusion from Distributed Databases and Knowledge Bases, In: Proceedings of Database and Expert System Applications Conference (DEXA’ 97), Toulouse, France, 1-5 September, pp. 682-691.
16.
Mészáros, T., Barczikay, Z., Bodon, F., Dobrowiecki, T.P. and Strausz, G. (2001). Building an Information and Knowledge Fusion System, In: Proceedings of IEA/AIE-2001, Budapest, Hungary , 4-7 June, pp. 82-91.
17.
Keen, P. and Tan, M. ( 2007). Knowledge Fusion: A Framework for Extending the Rigor and Relevance of Knowledge Management, International Journal of Knowledge Management, 3(4): 1-17.
18.
Smirnov, A., Pashkin, M., Chilov, N., Levashova, T. and Haritatos, F. ( 2002). A KSNet-approach to Knowledge Logistics in Distributed Environment, In: Proceedings of the International Conference on Human-Computer Interaction in Aerospace, MIT, Cambridge , Massachusetts, 23-25 October, pp. 88-93.
19.
Hunter, A. and Summerton, R. ( 2004). Fusion Rules for Context-dependent Aggregation of Structured News Reports, Journal of Applied Non-classical Logics, 14(3): 329-366.
20.
Hashemi, R. and Razzaghi, M. ( 1992). Conflict Resolution in Inductive Learning from Examples , In: Berghel, H., Deaton, E., Hedrick, G., Roach, D. and Wainwright, R. (eds), Proceedings of the 1992 ACM/SIGAPP Symposium on Applied Computing: Technological Challenges of the 1990s, Kansas City, MO, 01-03 March, pp. 598-602.
21.
Durand, N., Alliot, J.M. and Noailles, J. ( 1996). Automatic Aircraft Conflict Resolution using GA, In: George, K.M., Carroll, J.H., Oppenheim, D., Hightower, J. (eds), Proceedings of the 1996 ACM Symposium on Applied Computing, Philadelphia, PA, 17-19 February, pp. 289-298.
22.
Amgoud, L. and Kaci, S. ( 2007). An Argumentation Framework for Merging Conflicting Knowledge Bases, International Journal of Approximate Reasoning, 45: 321-340.
23.
Zadeh, L.A. (1989). Knowledge Representation in Fuzzy Logic, IEEE Transactions on Knowledge and Data Engineering , 1(1): 89-100.
24.
Leskovec, J., Milic-Frayling, N. and Grobelnik, M. ( 2005). Extracting Summary Sentences Based on the Document Semantic Graph, Microsoft Technical Report TR-2005-07.
25.
Bordogna, G. and Pasi, G. (1993). A fuzzy Linguistic Approach Generalizing Boolean Information Retrieval: A Model and its Evaluation, Journal of the American Society for Information Science, 44(2): 70-82.
26.
Caillaud, E. , Gourc, D. and Garcia, L.A. (1999). A Framework for a Knowledge-Based System for Risk Management in Concurrent Engineering, Concurrent Engineering: Research and Applications, 7(3): 257-267.
27.
Herrera, F. and Martinez, L. (2000). A 2-tuple Fuzzy Linguistic Representation Model for Computing with Words, IEEE Transactions on Fuzzy Systems, 8(6): 746-752.
