The Role of the Clusters Analysis Techniques to Determine the Quality of the Content Wiki

• Main Authors: Mouna Boulaajoul, Noura Aknin
• Format: Article
• Language: English
• Published: Kassel University Press 2019-01-01
• Series: International Journal of Emerging Technologies in Learning (iJET)
• Subjects: web 2.0; Wiki; data mining; cluster Analysis; k-Means algorithm; discretization; WEKA
• Online Access: http://online-journals.org/index.php/i-jet/article/view/9074

The online sources of the web, since years, are an extraordinarily important base of information and knowledge. Indeed, the web is one of the best access point to any type of information. For the users who want to share their knowledge, the wiki system is a powerful tool. Nevertheless, any system has its limits. The investigation on the contributions performance of individual contributors is yet unexplored because it is partly related to the design of wikis which is considered for collaborative work. Consequently, this has made the assessment and evaluation of individual contributions a hard task. In this research, we will attempt to emphasize the significance of distinguishing the relevant articles based on the opinions of contributors and their contributions. In this way, we will focus on the utilization of data mining using clusters analysis and k-means algorithm techniques.