Rule Based Expert System for Error Log Analysis
Omkar Patil1, Umesh Chavan2
1Omkar Patil, Department of Information Technology, Walchand College of Engineering, Sangli, India.
2Umesh Chavan, Department of Information Technology, Walchand College of Engineering, Sangli, India.
Manuscript received on July 07, 2020. | Revised Manuscript received on July 18, 2020. | Manuscript published on August 10, 2020. | PP: 188-192 | Volume-9 Issue-10, August 2020 | Retrieval Number: 100.1/ijitee.J74660891020 | DOI: 10.35940/ijitee.J7466.0891020
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Humans have been using their domain expertise intelligently and skillfully for making decisions in solving a problem. These decisions are made based on the knowledge that they have acquired through experience and practice over a course of time, which will be lost after the expert’s life ends. Hence, this expert knowledge is required to be stored to a database and a machine could be intelligently programmed which could use this knowledge to make decisions, known as an Expert System (ES). This system tries to emulate the decision-making skills of a domain expert by gathering knowledge of the domain experts, storing it to a knowledge base in rule format, and then using those rules to analyze the given data and provides solutions to the problems. These Expert Systems can be utilized to analyze the system log files, find issues logged into those log statements and provide solutions to the errors that are found in those logs.
Keywords: Artificial Intelligence, Expert System, Inference Engine, Knowledge base, Log Analysis, Log statements, Rules.
Scope of the Article: Artificial Intelligence