Search

In order to alleviate the user's " knowledge obsession" problem and improve knowledge application and innovation efficiency, this paper proposed a knowledge matching method that combined three-way decision and GRA-Orthopair fuzzy sets . First, this paper used CRITIC-entropy method for weight configuration, and integrated sgame theory methods to enhance the objective weighting effect ; then, it used the FCM clustering algorithm to compress the matching space horizontally; and then, it used the three-way decision ideas to implement pre-classification, considered the inter-knowledge relevance degree, constructed Orthopair fuzzy similarity model based on gray relevance degree, and calculated the view similarity between user needs and case knowledge based on this, so as to determine the matching result. Experimental results show that this algorithm is better than traditional matching algorithms in knowledge matching accuracy and efficiency,and improves the matching effect. [ABSTRACT FROM AUTHOR]