Models and methods for extracting and synthesizing knowledge from data

1. Higher education: 5. Technical sciences

2. Professional field: 5.2 Electrical engineering, electronics and automation

3. Doctoral program: Automated systems for information processing and management.

4. Form of training: full-time (officer or citizen outside the system of the Ministry of Defense, SPAM and BA)

5. Applicant: Defense Institute "Professor Tsvetan Lazarov"

6. Primary Unit: Communications and Information Systems and Information Protection Department

7. Accepting structural unit: Development of C4I Systems Directorate

8. Actuality and Disserability of the Suggested Scientific Problem:

The large amount of data that is produced and stored almost daily in arrays of various organizations and on the Internet contains correlations and dependencies, often avoided by traditional means of processing them. Retrieving the hidden knowledge in them is a prerequisite for helping make more accurate decisions and effectively manage the organization's resources.

The subject is dissertation with the possibility to study modern models, methods and algorithms for extracting and summarizing knowledge from structured and unstructured datasets, so called Data Mining and Data Fusion. The aim is to explore the processes of finding meaningful correlations, dependencies, repetitive patterns, trends, and anomalies in large arrays of information stored in databases and data warehouses by using techniques and algorithms in the field of machine learning, image recognition, statistics, neural networks, data visualization, etc. An important feature is the possibility of processing multi-dimensional arrays and extracting multidimensional relationships between different components and parameters to detect the hidden knowledge within them.

The aim of the study is to analyze existing models, methods and algorithms in the field and to offer new and effective solutions for data processing and knowledge extraction.

The results of the topic development will enable the scope of research in the field of data and knowledge processing to be explored, to explore existing and propose new methods, methodologies or algorithms and to support the decision-making process at the management level. This will also lead to the development of mathematical and applied means of implementing results in support of security and defense decision-making.