Recent advances in mining patterns from complex data

Data mining and knowledge discovery are advanced research fields with numerous algorithms and studies to extract patterns and models from complex data sources like blogs, event or log data, biological data, spatio-temporal data, social networks, mobility data, and sensor data and streams. The works presented in this special issue of the Journal of Intelligent Information Systems should keep the attention of both researchers and practitioners of data mining who are interested in the advances and latest developments in the area of extracting patterns. Behavioral Process Mining for Unstructured Processes by Claudia Diamantini, Laura Genga and Domenico Potena addresses the challenging problem of extracting useful information from the huge volume of events recorded by several of today's enterprise systems.