New cybercrime taxonomy of visualization of data mining process - Babic, M.; Jerman-Blazic, B. (2016 39th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), 2016)
Data Mining is the process of identifying new patterns, insights in data and knowledge discovery, and is at the intersection of multiple research areas, including Machine Learning, Statistics, Pattern Recognition, Databases, and Visualization. With the maturity of databases and constant improvements in computational speed, data mining algorithms that were too expensive to execute are now within reach. Data visualization is a general term that describes any effort to help people understand the significance of data by placing it in a visual context. Patterns that might go undetected in text-based data can be exposed and recognized easier with data visualization software. Exploring and analyzing the vast volumes of data becomes increasingly difficult. Information visualization and visual data mining can help to deal with the flood of information. There is a large number of information visualization techniques which have been developed over the last decade to support the exploration of large data sets. In this paper, we propose a classification of information visualization and visual data mining techniques. Fractals and graph theory are very popular in different areas. We present a new method for estimating fractal dimension for network and new Taxonomy of visualization of data mining process application in Cybercrime activity.