Leader: Ivan Koychev
Data analytics includes processing and analysis of data to improve data understanding and the meaningfulness of data. Data processing is related to data modelling, analysis and reasoning including semantic and knowledge-based analysis, scalable and incremental reasoning, linked data mining and cognitive computing.
Four types of Big Data analytics can be defined: Prescriptive Analytics, Predictive Analytics, Diagnostic Analytics and Descriptive Analytics.
Data Analytics is applied using online and scalable machine learning algorithms, which are able to continuously update the learned models and to work on distributed systems. At the same time, Real-time Data Analytics dramatically changes the ways systems can use data to predict outcomes and suggest alternatives. Instead of putting together conjectures based on a series of past events and recent scans, systems working in real-time can deliver insights on what is going on right now. In addition, new machine-learning systems have the ability to explain their rationale, characterize their strengths and weaknesses, and convey an understanding of how they will behave in the future.
Current Research Directions:
For further information: prof. Ivan Koychev, email: *protected email*