Training and Research Lab

Business Analysis, Artificial Intelligence and Decision Support Lab

The Laboratory is a structural subdivision of the Educational and Research Institute (hereinafter referred to as the Institute) of Computer Science and Information Technology of the National Technical University “Kharkiv Polytechnic Institute” (hereinafter referred to as the University, NTU “KhPI”), which is created to organize and conduct educational and research activities in the field of business analysis, artificial intelligence and decision support in cooperation with the Institute of Informatics of Istanbul Technical University (Turkey) with the support of the Ukrainian-Turkish Coordination Center for scientific and technical research of NTU “KhPI”.

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The laboratory carries out research, scientific, technical and educational activities in the following areas:

  • Data Warehousing;
  • On-Line Analytical Processing;
  • Uncertainty Analysis;
  • Business Intelligence;
  • Artificial Intelligence, Machine Learning, Computer Vision;
  • Business Process Modeling, Analysis, and Management;
  • Weak-structured Data Processing, Natural Language Processing;
  • Multi-Agent Systems;
  • Intelligent data Analysis, Data Mining;
  • Search Engine Optimization, Virtual Promotion.

Research and development work is performed in the laboratory by:

  • full-time scientific and engineering staff;
  • the teaching staff;
  • doctoral students, postgraduates, and students;
  • employees of other institutions on the basis of contracts or contractors’ agreements.
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Research projects of the Department of Software Engineering and Management Intelligent Technologies within the educational and scientific laboratory of business analysis, artificial intelligence and decision support
piitu_lab_proposals
Eugene Turkestanov, Managing Partner у Silver Phoneix Consulting (Calgary, Alberta, Canada) gave a feedback on the educational and research laboratory of business analysis, artificial intelligence and decision support
Scientific papers of the staff of the SEMIT Department in the field of lab work
  1. Towards Classifying HTML-embedded Product Data Based On Machine Learning Approach
  2. Multi-Agent Modeling of Project Management Processes in Distributed Teams
  3. Improving Item Searching On Trading Platform Based On Reinforcement Learning Approach
  4. Advanced Method of Synthesis of Semantic Kernel of E-content
  5. Towards Understandability Evaluation of Business Process Models using Activity Textual Analysis
  6. A New Method of Search Engine Optimization Based on Semantic Kernel Idea
  7. A New Approach to Search Engine Optimization Based on the Synthesis of a Virtual Promotion Map
  8. A Method for Evaluating the Efficiency of the Semantic Kernel in the Internet Promotion Channel
  9. Map of Virtual Promotion of a Product
  10. Analysis of virtual promotion of a product
  11. Towards an Approach to Organization of Decentralized Business Process Model Repository
  12. Mathematical Model of Semantic Kernel of WEB site
  13. An Approach and Software Prototype for Translation of Natural Language Business Rules into Database Structure
  14. Software Development for Semantic Kernel Forming
  15. Using Internet News Flows as Marketing Data Component
  16. An Approach to Development of Interactive Adaptive Software Tool to Support Data Analysis Activity
  17. Towards the Method and Information Technology for Evaluation of Business Process Model Quality
  18. An Approach to Business Process Model Structuredness Analysis: Errors Detection and Cost-Saving Estimation
  19. Towards the Tokenization of Business Process Models using the Blockchain Technology and Smart Contracts
  20. An Information Technology for Detection and Fixing Effort Estimation of Business Process Model Structuredness Errors
  21. Towards the Enterprise Architecture Web Mining Approach and Software Tool
  22. Towards Intelligent Technology for Error Detection and Quality Evaluation of Business Process Models
  23. Computational Technology and Software Tool for Translation of Business Rules into Database Creation Scripts
  24. Towards the Software Solution for Complexity Minimization of Business Process Models to Improve Understandability
  25. Towards Software Development for Maintainability Evaluation of Business Process Models Using Fuzzy Logic
  26. Fuzzy Logic-based Software Tool for Business Process Model Complexity Assessment
  27. Researching a machine learning algorithm for a face recognition system
  28. Smart Grid and wind generators: an overview of cyber threats and vulnerabilities of power supply networks
  29. DEVELOPMENT OF THE AUTOMATED DECISIONMAKING SYSTEM SYNTHESIS METHOD IN THE MANAGEMENT OF INFORMATION SECURITY CHANNELS
  30. Designing and evaluating dl-model for vulnerability detection in smart contracts
  31. Integrating analytical statistical models, sequential pattern mining, and fuzzy set theory for advanced mobile app reliability assessment
  32. Comparison of machine learning methods for a diabetes prediction information system
  33. Analysis of statistical indicators of variance, asymmetry and excess in determining information security violations of cyberphysical systems of wind turbines

Head of the educational and research lab

Doctor of Physical and Mathematical Sciences, Professor VELIIEV Eldar Ismail ogly

eldar.veliev@khpi.edu.ua