Knowledge communication analysis based on clustering and association rules mining

Author(s)
Wang, Philips Fu Lee
Author(s)
Wu, Q.
Wu, Q.
Zhao, S.
Wei, M.
Date Issued
2015
Publisher
Springer
Related Publication(s)
Database Systems for Advanced Applications (DASFAA 2015 International Workshops) Revised Selected Papers
Start page
66
End page
75
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.
URI
DOI
SFU Affiliated Publication
Yes
Availability at SFU Library

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