Remedial Solutions to Improve the Efficiency of Knowledge Based Systems
DOI:
https://doi.org/10.26438/ijcse/v7i6.720724Keywords:
Knowledge Base System, Expert System, Inference Engine, Knowledge Acquisition, Concept DevelopmentAbstract
A learning base is an effectively available information stockpiling center that contains data about a specific item, administration, theme, or idea. Associations make learning bases to house the majority of the information inside their association about a specific subject, to give one area to get to this data. Information bases can target inside representatives (on account of an organization learning base) or the general population - clients or potential clients - who need to study a specific item, subject, or idea. The objective of a learning base is to legitimately give data to these clients, and, on account of an interior framework, to expand the general comprehension of the whole association. Designing and development of a efficient knowledge base system is a challenging task. In this paper author describe the challenges for KBS and failure of KBS and its causes. Author also provide a deep insight the remedial solution to improve the efficiency of a KBS.
References
[1]. Hemant Kumar Soni, S. Sharma, and M. Jain, “Frequent Pattern Generation Algorithms for Association Rule Mining : Strength and Challenges”, In: Proc. of IEEE International Conference on Electrical, Electronics and Optimization Techniques, pp. 3744-3747, 2016.
[2]. Hemant Kumar Soni, S. Sharma and M Jain, “Plausible Characteristics of Association Rule Mining Algorithms for E-Commerce”, In: Proc. of the 3rd International Conference on Advances in Electrical, Electronics, Information, Communication and Bio-Informatics, pp. 36-39, 2017.
[3]. ITL ESL, Introduction to Information Technology, Chapter 22.
[4]. N. Mishra, H. K. Soni, S. Sharma and A K Upadhyay, “A Comprehensive Survey of Data Mining Techniques on Time Series Data for Rainfall Prediction”, Journal of ICT Research and Applications, Vol.11, No.2, p 2017p. 167-183,.
[5]. Hemant Kumar Soni, S. Sharma, AK Upadhyay, “An empirical algorithm for high and low correlative association rule mining”, International Journal of Intelligent Engineering Systems, Vol. 11, Issue 3, , pp 223-232, 2018.
[6]. Russell .S, and P.Norvig, Artificial Intelligence: A modern approach, Second Edition, Prentice-Hall, New Delhi. 2002.
[7]. Dennis Ritchie, Artificial Intelligence, Tata McGraw-Hill, New Delhi. 1996
[8]. K. P. Tripathi, “A review on knowledge-based Expert System: Concept and architecture.” IJCA Special issues on Artificial intelligence techniques, pp19-23, 2011.
[9]. Avram Gabriela, “Empirical Study on Knowledge Based Systems, The Electronic Journal of Information Systems Evaluation, Vol 8.Iss 1, pp. 11-20, 2005.
[10]. Eliciting, collecting and developing requirements, available at https://www.mitre.org/publications/systems-engineering-guide/se-lifecycle-building-blocks/requirements-engineering/eliciting-collecting-and-developing-requirements
[11]. Software and Artificial Intelligence, Executive summary, NESSI, issue 1, pp 1-6., 2019.
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