Case Studies in Data Mining

In these university textbooks, we present basic concepts in the field of networks and graph theory. We search for graphs in width and depth. We present static and dynamic network models. We describe the issue of detecting overlapping and non-overlapping communities in oriented and non-oriented networks. Different approaches to network anomaly detection also form an important part of this textbook. The final chapter is devoted to spectral clustering, which plays an important role in data mining in network graphs for different application domains. Teaching texts are suitable for students of computer science departments of the first and second level of universities. Study materials are also suitable for students of non-informatics disciplines with a view to improving their knowledge and practical experience in the fields of informatics and provide an opportunity for students to apply in IT companies in solving practical tasks.