References: [1] Adam, F. (2012). 20 years of decision making and decision support research published by the Journal of Decision Systems. Journal of Decision Systems, 21 (2) 93-99. [2] Ackerman, M. S., Halverson, C. A. (2004). Organizational Memory as Objects, Processes, and Trajectories: An Examination of Organizational Memory in Use. Computer Supported Cooperative Work (CSCW), 13, 155–189. [3] Aamodt, A., Plaza, E. (1994). Case-based reasoning: foundation issues, methodological variations and system approaches. Artificial Intelligence Communications, 7, 39-59. [4] Guo, Y., Hu, J., Peng, Y. (2012). A CBR system for injection mould design based on ontology: A case study. Computer-Aided Design, 44, 496–508. [5] Gallupe, B. (2001). Knowledge management systems: surveying the landscape. International Journal of Management Reviews, 3 (1) 61-77. [6] Alavi, M., Leidner, D. E. (2001). Knowledge Management and Knowledge Management Systems: Conceptual Foundations and Research Issues. Management Information Systems (MIS), 1 (10) 107-136. [7] Maier, R., Hadrich, T. (2011). Knowledge Management Systems. Encyclopedia of Knowledge Management, Second Edition, IGI Global, 779-790. [8] Tan, F. B., Gallupe, R. B. (2008). Global information management research: current status and future directions. In Tan, FB (ed.): Global Information Technologies: Concepts, Methodologies, Tools, and Applications, 3571- 3584, IGI Global. [9] Lamontagne, L., Plaza, E. (2014). Case-Based Reasoning Research and Development. LNCS 8765, Springer International Publishing Switzerland. [10] Richter, M. R., Weber, R. O. (2013). Case-Based Reasoning: A Textbook. Springer-Verlag Berlin Heidelberg. [11] Ming, Z., Sharma, G., Allen, J. K., Mistree, F. (2020). An Ontology for Representing Knowledge of Decision Interactions in Decision-Based Design. Computers in Industry, 114, 103145. [12] Antoniou, G., Harmelen, F. (2004). A Semantic Web. Primer, MIT. [13] Park, G., Benedictos, R. M., Lee, C., Wang, M. H. (2007). Ontology-Based Fuzzy-CBR Support System for Ship’s Collision Avoidance. In: Proc. of International Conference on Machine Learning and Cybernetics (ICMLC.2007), pages 1845-1850, Hong Kong, (August). [14] Benmessaoud, N., Adla, A. (2019). Intelligent Semantic Case Based Reasoning System for Fault Diagnosis. Journal of Digital Information Management (JDIM), 17 (2) 75-86. [15] Garrido, J. L., Hurtado, M. V., Noguera, M., Zurita, J. M. (2008). Using a CBR approach based on ontologies for recommendation and reuse of knowledge sharing in decision making. In: Proc. of 8th International Conference on Hybrid Intelligent Systems (HIS 2008), pages 837–42, Barcelona, (September). [16] Wang, D., Xiang, Y., Zou, G., Zhang, B. (2009). Research on Ontology-Based Case Indexing in CBR. In: Proc. of International Conference on Artificial Intelligence and Computational Intelligence (AICI.2009), pages 238-241, Shanghai, (January). [17] Kobti, Z., Chen, D (2010). A domain ontology model for mold design automation, Canadian AI, 6085, 336–339. [18] J. Rockwell, J., Grosse, I. R., Krishnamurty, S., Wileden, J. C. (2009). A Decision Support Ontology for collaborative decision making in engineering design. In Proc. of 2009 International Symposium on Collaborative Technologies and Systems (CTS 2009), pages 1-9, Baltimore, (May). [19] Gaillard, E., Infante-Blanco, L., Lieber, J., Nauer, E. (2014) Tuuurbine: A Generic CBR Engine over RDFS. In: Lamontagne L., Plaza E. (eds) Case-Based Reasoning Research and Development. (ICCBR 2014), Lecture Notes in Computer Science, 8765, Springer, Cham. [20] Zhukova, I., Kultsova, M., Navrotsky, M., Dvoryankin, A. (2014). Intelligent Support of Decision Making in Human Resource Management Using Case-Based Reasoning and Ontology. In: Kravets A., Shcherbakov M., Kultsova M., Iijima T. (eds) Knowledge-Based Software Engineering, Communications in Computer and Information Science, 466. Springer, Cham. [21] Bumblauskas, D., Gemmill, D., Igou, A., Anzengruber, J. (2017). Smart Maintenance Decision Support Systems (SMDSS) based on corporate big data analytics. Expert Systems with Applications, 90, 303–317. [22] Shana, W., Dongbob, L., Gaoc, J., Jinga, L (2019). A knowledge based machine tool maintenance planning system using case-based reasoning techniques. Robotics and Computer Integrated Manufacturing, 58, 80–96. [23] Maa, Z., Rena, Y., Xianga, X., Turk, Z. (2020). Datadriven decision-making for equipment maintenance. Automation in Construction, 112, 1-17. [24] Adla, A., Soubie, JL., Zaraté, P (2007). A cooperative Intelligent Decision Support System for Boilers Combustion Management based on a Distributed Architecture. Journal of Decision Systems (JDS), 16 (2) 241-263. [25] Adla, A., Zarate, P., Soubie, J. L. (2011). A Proposal of ToolKit for GDSS Facilitators. Group Decision and Negotiation (GDN), 20, 57-77. [26] Sure, Y., Staab, S., Studer, R. (2009). Ontology Engineering Methodology. In: Staab S., Studer R. (eds) Handbook on Ontologies. International Handbooks on Information Systems, Springer, Berlin, Heidelberg. [27] Cormicana, K., Yub, M (2019). Ontology-based systems engineering: A state-of-the-art review. Computers in Industry 111, 148–171. [28] Hitzler, P., Krötzsch, M., Parsia, B., Patel-Schneider, P. F., Rudolph, S (2012). OWL 2 web ontology language: document overview, W3C Recommendation, http://www.w3.org/TR/owl2-overview/. [29] Schildt, H. (2014). Java: The Complete Reference, McGraw-Hill Education Group. [30] Jena, (2019). A free and open source Java framework for building Semantic Web and Linked Data applications. HP Labs, ena.apache.org. [31] Pan, J. Z. (2009). Resource Description Framework. In: Staab S., Studer R. (eds) Handbook on Ontologies. International Handbooks on Information Systems, Springer, Berlin, Heidelberg. [32] Prud’hommeaux, E., Seaborne, A. (2008). SPARQL Query Language for RDF. W3C, http://www.w3.org/TR/rdfsparql-query/ |