Knowledge Checking Service Selection Method in Pythagorean Fuzzy Environment

Abstract

Knowledge checking service is very important for safeguarding the quality of the knowledge in the knowledge repository. There are many knowledge checking services with similar functions but different qualities in organizations, especially in the crossing organizations. It is not easy to measure the non-functional criteria because of the complexity and the involvement of user's fuzzy perceptions of knowledge checking services. In order to help the evaluation and selection of the knowledge checking services, the knowledge checking services selection method in Pythagorean fuzzy environment is developed. Firstly, decision makers use linguistic terms to express their preferences on the alternative knowledge checking services with respect to each criterion. Afterwards, the linguistic terms are transformed into the Pythagorean fuzzy forms. Then the collective opinions are derived by aggregating the opinion given by each decision maker. After calculating the degree of linguistic grey relational coefficient of each alternative from PIS and NIS, the relative relational degree of each alternative from PIS are derived. Then all the alternatives are ranked in accordance with the relative relational degree in descending order. The illustrative example of knowledge service selection shows the proposed method is feasible and efficient.