Knowledge Extraction Model

Purpose: Considering the development of technology and the use of artificial intelligence in the process of knowledge management in the service sector as well as intelligent knowledge extraction, this study aims to model an intelligent knowledge extraction map to make value in organizations. Method: This research is applied and survey. Ten influential components in knowledge extraction were identified through library study. The study sample was selected using the judgmental sampling method of five person. Using the Delphi technique, screening and evaluation of the identified components have been done. The interpretive structural model method was used to model the knowledge extraction map. The software used is EXCEL and MATLAB. Findings: The findings show that Intelligent measurement and organization of knowledge is in the second level. Five phases have been obtained for the initial steps of the Knowledge Extraction Model in service organizations. Intelligent measurement and organization of knowledge in the first phase, identifying external factors, identifying internal factors, and Identifying necessary actions in the second phase, Organization of knowledge processes, Organizing the necessary infrastructure in the third phase, Targeting knowledge and Smart knowledge strategy in the fourth phase, and finally Monitoring and updating knowledge, and Evaluating intelligent knowledge extraction in the fifth phase are main steps in the knowledge extraction model. Conclusion: To achieve success in the service sector, knowledge extraction is required to make managers able to decide better. To begin intelligent knowledge extraction, we need to follow five essential and initial steps to prepare the organization for this process.