Usable, Flexible and Adaptive Network Data Visualization Design for Multiple Levels of Computer Users

Numerous Network Data Visualization Tools have been developed to visually analyze and visualize multivariate data. However, these conventional network data visualization tools are typically designed with network administrators (advanced users) in mind. In this paper, we construct an adaptive visualization tool in order to solve the demands of different computer users. We adopted three supervised algorithms for our framework, namely Naive Bayes (NB), C4.5, and Support Vector Machine (SVM). Our experiment showed that the proposed framework not only managed to produce a usable interface but also has better visualization compared to existing network data visualization applications. Moreover, it is able to present comprehensive network data and is capable of adapting to user feedback during the network data visualization process. This intelligence enables the framework to adjust to the needs of different computer users when they perform network data visualization.