In the era of overinformation and content abundance, research faces the challenge of providing actionable insights and knowledge from the underlying wealth of information. The challenge is directly related to whether we can efficiently query, analyse, interprete and visualize data in a way that will be usable by both experts and non-experts. The multi-modal nature of the data people share and interact upon poses another difficulty to the analysis process. Essentially, in order to face the challenge, experts from different disciplines need to join forces.
Given this real need, the CAKT group brings together researchers and developers covering a variety of domains related to Natural Language Processing, Data Mining, Machine Learning, Knowledge Representation and Visualization under a common aim. The aim is to develop top-notch, scalable and widely adoptable methods and system solutions for multi-modal content analysis (e.g. text, image, speech, video), knowledge representation and management.