Abstract
Various expert system development approaches were proposed but most of them cannot deal with two problems: the difficulty of analysis and maintenance. Rather than to spend time waiting any longer, it is better to find an alternative solution from other research fields. In computer software development area, researchers have been suffering from the difficulty of maintenance and analysis, just as the researchers in the expert system development field. To solve this issue, researchers in the software used both agile software development and business rules approach: agile software development is for overcoming the the difficulty of analysis, and business rules approach is for reducing issues in the maintenance. There is a big opportunity that those two approaches can also be solve the two issues in the expert system development field. The paper describes requirements of the approach based on agile software development and the business rules approach. As a result, we consider and specify why the Multiple Classification Ripple Down Rules is the novel approach for the expert system development.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Abdelhamid Y, Hassan H, Rafea A (1997) A proposed methodology for expert system engineering. In: 5th International conference on artificial intelligence applications. Egyptians Computer Society, Cairo, Egypt
Amine M, Ahmed-Nacer M (2011) An agile methodology for implementing knowledge management systems: A case study in component-based software engineering. Softw Eng Appl 5(4):159–170
Baumeister J, Puppe F, Seipel D (2004) An agile process model for developing diagnostic knowledge systems. Kunstliche Intelligenz 18(3):12–16
Bindoff I, Kang B, Ling T, Tenni P, Peterson G (2007) Applying mcrdr to a multidisciplinary domain. AI 2007: Advances in, Artificial Intelligence, pp 519–528
Blythe J, Kim J, Ramachandran S, Gil Y (2001) An integrated environment for knowledge acquisition. In: Proceedings of the 6th international conference on Intelligent user interfaces, ACM, pp 13–20
Burman S, Kim Y, Kang B, Park G (2006) Maintenance of game character’s ai by players. Int J Multimedia Ubiquitous Eng 1(1):39–46
Cao T, Martin E, Compton P (2004) On the convergence of incremental knowledge base construction. In: Discovery Science, Springer, pp 505–584
Compton P, Jansen R (1990) A philosophical basis for knowledge acquisition. Knowledge acquisition 2(3):241–258
Compton P, Peters L, Edwards G, Lavers T (2006) Experience with ripple-down rules. Knowl Based Syst 19(5):356–362
Das P, Bhattacharyya D, Bandyopadhyay S, Kim T (2009) Analysis and diagnosis of breast cancer. u - and e - Service. Sci Technol 2(3):1–12
Grossner C, Preece A, Gokul Chander P, Radhakrishnan T, Suen C (1993) Exploring the structure of rule based systems. In: Proceedings of the national conference on artificial intelligence, Wiley, pp 704–704
Han S, Chung H (2012) Social issue gives you an opportunity: Discovering the personalised relevance of social issues. Knowl Manage Acquisition Intell Syst 7457:272–284
Hazzan O, Dubinsky Y (2007) Why software engineering programs should teach agile software development. ACM SIGSOFT Softw Eng Notes 32(2):1–3
Jimènez Guarín C, Gòmez J (2010) Genesis: Agile generation of information management oriented software. Revista de Ingeniería 31:30–39
Kajko-Mattsson M (2008) Problems in agile trenches. In: Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement, ACM, pp 111–119
Kang B (1996) Validating knowledge acquisition: multiple classification ripple-down rules. PhD thesis, University of New South Wales
Kang B, Compton P, Preston P (1995) Multiple classification ripple down rules: evaluation and possibilities. In: The 9th knowledge acquisition for knowledge based systems workshop
Kang B, Gambetta W, Compton P (1996) Verification and validation with ripple-down rules. Int J Human-Comput Stud 44(2):257–269
Kim Y, Kang B (2008) Search query generation with mcrdr document classification knowledge. Practice and Patterns, Knowledge Engineering, pp 292–301
Mateo R, Lee J, Gerardo B (2008) Healthcare expert system based on group cooperation model. Softw Eng Appl 2(1):105–116
Miranda-Mena T, Benítez US, Ochoa J, Martínez-Béjar R, Fernández-Breis J, Salinas J (2006) A knowledge-based approach to assign breast cancer treatments in oncology units. Expert systems with applications 31(3):451–457
Mohammad A, Al Saiyd N (2010) A framework for expert knowledge acquisition. IJCSNS 10(11):145
Park S, Kim Y, Kang B (2004) Web document classification: Managing context change. In: IADIS International Conference WWW/Internet, pp 143–151
Piaget J, Vonèche J (2007) The child’s conception of the world. Rowman & Littlefield Pub Incorporated, Lanham
Rao K, Kavita Naidu G (2011) A study of the agile software development methods, applicability and implications in industry. Softw Eng Appl 5(2):35–46
Schreiber G, Wielinga B, de Hoog R, Akkermans H, Van de Velde W (1994) Commonkads: a comprehensive methodology for kbs development. IEEE Expert 9(6):28–37
Vazey M, Richards D (2005) Troubleshooting at the call centre: a knowledge-based approach. In: Proceedings of the Artificial Intelligence and Applications
Wobcke W, Chan R, Limaru A, (2006) A call handling assistant for mobile devices. In: Intelligent Agent Technology, (2006) IAT’06. IEEE/WIC/ACM International Conference on IEEE, pp 717–722
Zelkowitz M, Yeh R, Hamlet R, Gannon J, Basili V (1984) Software engineering practices in the USA and Japan. Computer 17(6):57–70
Acknowledgments
This paper was supported by Australian Research Council (ARC) and Asian Office of Aerospace Research and Development (AOARD).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Han, S.C., Yoon, HG., Kang, B.H. et al. Using MCRDR based Agile approach for expert system development. Computing 96, 897–908 (2014). https://doi.org/10.1007/s00607-013-0336-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00607-013-0336-y