Knowledge communication analysis based on clustering and association rules mining

Abstract

With the growth of knowledge sharing, an increasingly large amount of Open-Access academic resources are being stored online. This paper systematically studies the method of mining knowledge communication via Open-Access Journals. We first designed a new framework of knowledge communication analysis based on clustering and association rule mining. Then, we proposed two improved indexes named cited frequency and weighted cited frequency. Extensive evaluations using real-world data validate the effectiveness of the proposed framework of knowledge communication analysis.