Data Streams are environments where data is generated at high volume and speed. Data stream models are subjected to resource constraints such as time and memory limitations. Additionally, the distribution of data can change over time (concept drifts). Our research topics in data stream mining include but not limited to concept drift detection, ensemble learning in evolving streams, multi-label stream classification, ensemble pruning in streams and so on.
Stylometry is the study of variations of linguistic style in written language by rigorous analysis of patterns and structures in texts. TO BE FILLED…