Externalization Method of Interval-Oriented Tacit Knowledge to Explicit Knowledge Concerning Multidimensional Algorithm Condition

Knowledge management has become increasingly important for organizations as it is a key element in employee retention strategies. By creating a culture of knowledge-sharing and collaboration, organizations can increase employee engagement and job satisfaction. This, in turn, leads to higher employee retention rates as employees are more likely to stay in an organization that values their knowledge and expertise. Unfortunately, experts are often unwilling to share their knowledge, either explicitly or tacitly, for various reasons. Because of this, it is difficult to acquire tacit knowledge or convert it into explicit knowledge. According to existing literature, a large amount of research has been done about externalization for converting tacit knowledge to explicit knowledge; however, their methodology is too basic and does not take into account the angular parameter of the tacit knowledge vector similarity algorithm, which reduces the effectiveness of the conversion. This research introduces a set of matching algorithms for explicit cases of tacit knowledge, with regards to the similarity condition of explicit cases of tacit knowledge. To optimize strong objectivity, rough set and entropy weight method is used to calculate the interval aspect weight with focus on complementary advantages. Next, optimal dispersion is used to improve the weight fusion optimization's time interval. Lastly, the Degree of Calculation Method determines the similarity of the case view. Based on the result of the similarity calculation, the historical case which is the same or has the highest similarity to the problem being solved is identified. The results of the case study show that the algorithm designed in this paper is effective and practical. This research can be beneficial in a knowledge management system, as it can recover and combine the implicit knowledge into interval-oriented knowledge, with the help of interval-based explicit case matching vector algorithms.