A knowledge-based expert system for campus helpdesk request processing

Help desks play a crucial function in the information technology department by acting as the main point of solution to customers’ issues. The speed and efficiency of agent-centric help desks are diminished by the inability of a help desk agents to share their knowledge when they leave and the inability of agents applying past cases to solve present problem. In this study, a knowledge-based expert system for campus helpdesk request processing was presented. The presented system consists of a fusion of expert system and fuzzy inference system for campus helpdesk request processing. The fuzzy inference system is responsible for the rules while the expert system provided the interface for the user interactions. The presented system takes input queries from students through the interface of the expert system. The input queries are converted into fuzzy variables and the inference engine is then used to compare the fuzzy variables with the fuzzy rules in the knowledge base of the expert system. The database base of the expert system contains the solutions to past queries while the rule base is made up of the set of IF-THEN rules depicting the domain expert knowledge. The expert system will fire the rules that matches the input queries and deliver the answers to the queries through the expert system output interface. The evaluation results of the presented system when compared with previous research showed a better accuracy of 95.36767% in terms of its efficiency in providing solutions to requests relating to complaints from campus students.