Automatic Rule Generator via FP-Growth for Eye Diseases Diagnosis
How to cite (IJASEIT) :
A. Dong and A. M. Agogino, “Text analysis for constructing design representations,” Artificial Intelligence in Engineering. vol. 11, pp. 65-75, 1997.
L. Millette, “Improving the Knowledge-Based Expert System Lifecycle,” Master's Thesis, University of North Florida, U.S., 2012.
W. Rui and L. Duo, “The study on the construction of knowledge base of grinding expert system based on data mining,” in International Conference on Mechatronic Science, Electric Engineering and Computer (MEC), 2011, p. 845-848.
M. Golabchi, “A knowledge-based expert system for selection of appropriate structural systems for large spans,” Asian Journal of civil engineering (Building and Housing)., vol. 9, pp. 179-191, 2008.
S. Mertens, M. Rosu, and Y. Erdani, “An intelligent dialogue for online rule-based expert systems,” in Proceedings of the 9th international conference on intelligent user interfaces, 2004, p. 280-282.
W. P. Wagner, “Issues in knowledge acquisition,” in Proceedings of the 1990 ACM SIGBDP conference on Trends and directions in expert systems, 1990, p. 247-261.
R. Kurniawan, N. Yanti, and M. Z. Nazri, “Expert systems for self-diagnosing of eye diseases using Naí¯ve Bayes,” in International Conference of Advanced Informatics: Concept, Theory and Application (ICAICTA), 2014, p. 113-116.
R. Mokhtar, N. A. M. Zin, and S. N. H. S. Abdullah, “Rule-based knowledge representation for modality learning style in AIWBES,” in Knowledge Management International Conference, 2010.
D.-L. Ma, W.-J. Zhang, B. Dong, P. Yang, and H.-X. Lu, “Establishing knowledge base of expert system with association rules,” in International Conference on Machine Learning and Cybernetics, 2008, p. 1785-1788.
M. Karabatak and M. C. Ince, “An expert system for detection of breast cancer based on association rules and neural network,” Expert systems with Applications. vol. 36, pp. 3465-3469, 2009.
S. M. Fakhrahmad, M. H. Sadreddini, and M. Zolghadri Jahromi, “A proposed expert system for word sense disambiguation: deductive ambiguity resolution based on data mining and forward chaining,” Expert Systems., vol. 32, pp. 178-191, 2015.
S.-S. Weng, S.-C. Liu, and T.-H. Wu, “Applying Bayesian network and association rule analysis for product recommendation,” International Journal of Electronic Business Management., vol. 9, pp. 149, 2011.
A. Ikram and U. Qamar, “A rule-based expert system for earthquake prediction,” Journal of Intelligent Information Systems., vol. 43, pp. 205-230, 2014.
Z. A. Othman, N. Ismail, and M. T. Latif, “Association rules of temperature towards high and low ozone in Putrajaya,” in 6th International Conference on Electrical Engineering and Informatics (ICEEI), 2017, p. 1-5.
M. F. M. Mohsin, A. A. Bakar, and M. H. A. Wahab, “A Comparative Study of Apriori and Rough Classifier for Data Mining,” Asia-Pacific Journal of Information Technology and Multimedia. vol. 5, 2008.
A. S. Saabith, E. Sundararajan, and A. A. Bakar, “Parallel implementation of apriori algorithms on the Hadoop-MapReduce platform-an evaluation of literature,” Journal of Theoretical and Applied Information Technology., vol. 85, pp. 321, 2016.
N. G. Noma and M. K. A. Ghani, “Discovering pattern in medical audiology data with FP-growth algorithm,” in Conference on Biomedical Engineering and Sciences (IECBES), 2012, p. 17-22.
A. S. Hoque, S. K. Mondal, T. M. Zaman, P. C. Barman, and M. A.-A. Bhuiyan, “Implication of association rules employing FP-growth algorithm for knowledge discovery,” in 14th International Conference Computer and Information Technology (ICCIT), 2011, p. 514-519.
J. W. Buckley, M. H. Buckley, and H.-F. Chiang, Research methodology and business decisions, 1976.
R. Kurniawan, M. Z. A. Nazri, M. Irsyad, R. Yendra, and A. Aklima, “On machine learning technique selection for classification,” in International Conference on Electrical Engineering and Informatics (ICEEI), 2015, p. 540-545.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).