The broad scope of DISA is to explore theories and technologies for next generation similarity search. This should be able to deliver relevant information effectively and efficiently to interested parties in the presence of exponentially growing volume, variety, and velocity of digital data. The DISA objectives are foundational in nature – they address the theoretical limits of similarity search in context of the Big Data Problem, considering the multimedia data as the primary proof of concept platform. The laboratory includes not only active researchers working on projects, but closely cooperates with students and disseminates results in practice.
The topics and objectives of the DISA lab can be summarized as follows:
- databases and data processing
- similarity indexing and searching
- content-based multimedia searching
- Big Data Phenomenon
- processing of biometric data (face recognition, movement characteristics)