Intelligent Semantic Systems
integration of machine learning approaches, such as artificial neural networks models with semantic models on the universal formal basis
About Project
The main goal of developed project is the creation of global distributed intelligent system, that consists of compatible cooperating intelligent systems, connected into cloud with Technology core. The Technology core includes actual versions of all components, used by interconnected systems. Semantic compatibility of systems allow to perform component actualization automatically, so every system in every moment has access to the most stable version of underlying platform and all components it needs.
The basic ideas of project are:
Integration of machine learning approaches, such as artificial neural networks models with semantic models on the universal formal basis
Information security:
All changes are automatically verified
Private information is stored on owner's server
No changes can be made without logging
Binary and human-readable dumps by schedule
Each system may share part if stored information to become reliable trustable source of information in some subject domain. So complex problem may be solved by using information from several systems
The system becomes a secure
repository of relable
objectiveinformation
repository of relable
objectiveinformation
Ensuring the reliability of
information obtained from
various sources
information obtained from
various sources
Use of distibuted ledger
technologies (DLT)
technologies (DLT)
Automation of the process of
analyzing the quality of
stored information
analyzing the quality of
stored information
Impossibility of intentional or
accidental distortion of
information
accidental distortion of
information
Use of distibuted ledger
technologies (DLT)
technologies (DLT)
Fixation of all system
changes in its knowledge base
changes in its knowledge base
Automation of the process of
analyzing the quality of stored
information
analyzing the quality of stored
information
Errors count reduction
No duplication of information
Automation of the process of
analyzing the quality of
stored information
analyzing the quality of
stored information
Reducing the costs of updating
and expanding information
resources
and expanding information
resources
Low laboriousness of stored
information correction,
including knowledge bases
tructure correction
information correction,
including knowledge bases
tructure correction
Ease of stored information
updating, including
automation of this process
updating, including
automation of this process
Company information is used
much more efficiently
much more efficiently
Search for the necessary
information for all types of
users is simplified
information for all types of
users is simplified
The ability to store
meta-information at any
level
meta-information at any
level
The ability to automatically
identify the most important
information fragments
identify the most important
information fragments
The ability to structure a
knowledge base by
anunlimited number of
attributes
knowledge base by
anunlimited number of
attributes
No duplication of information
Each user receives only the
information that he
currently needs
information that he
currently needs
The ability to store
meta-information at any
level
meta-information at any
level
The ability to automatically
identify the most important
information fragments
identify the most important
information fragments
The ability to structure a
knowledge base by anunlimited
number of attributes
knowledge base by anunlimited
number of attributes
Automation of the business
processes
processes
The ability to store
meta-information at any
level
meta-information at any
level
No duplication of information
Automation of the process of
analyzing the quality of stored
information
analyzing the quality of stored
information
Ease of stored information
updating, including
automationof this process
updating, including
automationof this process
Employees work load
optimization
optimization
The ability to store
meta-information at any
level
meta-information at any
level
The ability to automatically
identify the most important
information fragments
identify the most important
information fragments
No duplication of information
Automation of the process of
analyzing the quality of
stored information
analyzing the quality of
stored information
Low laboriousness of stored
information correction,
including knowledge base
structure correction
information correction,
including knowledge base
structure correction
Ease of stored information
updating, including
automation of this process
updating, including
automation of this process
Reducing the costs of updating
and expanding information
resources
and expanding information
resources
The ability to structure
aknowledge base by an unlimited number of attributes
aknowledge base by an unlimited number of attributes
No duplication of information
Automation of the process of
analyzing the quality of stored
information
analyzing the quality of stored
information
Low laboriousness of stored
information correction,
including knowledge base
structure correction
information correction,
including knowledge base
structure correction
Ease of stored information
updating, including
automation of this process
updating, including
automation of this process
Reduced costs for the study of
the system by users (both
employees and customers)
the system by users (both
employees and customers)
The ability to ask questions
about the system itself
about the system itself
Possibility of dialogue in a
language close to natural
language close to natural
System can be unlimitedly
improved and
intellectualized
improved and
intellectualized
Expanding the variety of
questions, which may
beasked to the system
questions, which may
beasked to the system
Low laboriousness of the
system functionality
expanding
system functionality
expanding
The possibility of step-by-step
intellectualization without any
restrictions
intellectualization without any
restrictions
Low laboriousness of system
adaptation to new tasks
adaptation to new tasks
System maintenance and
development costs are
significantly reduced
development costs are
significantly reduced
No duplication of information
Automation of the process
of analyzing the quality of
stored information
of analyzing the quality of
stored information
Low laboriousness of stored
information correction,
including knowledge base
structure correction
information correction,
including knowledge base
structure correction
Ease of stored information
updating, including
automationof this process
updating, including
automationof this process
Low laboriousness of the
system functionality
expanding
system functionality
expanding
The possibility of step-by-step
intellectualization without any
restrictions
intellectualization without any
restrictions
Low laboriousness of system
adaptation to new tasks
adaptation to new tasks
Technology
As a basis for the design of semantically compatible computer systems, we work with open semantic technology for intelligent systems (OSTIS technology).
The basis of this technology is SC-code - a standard for the semantic representation of information that basically uses set theory and graph theory.
The basis of this technology is SC-code - a standard for the semantic representation of information that basically uses set theory and graph theory.
The basis of OSTIS technology is the SC code - the standard of semantic representation of information in the memory of systems developed by us. The special feature of the SC-code is that it is language based on the set theory and made up of only 5 elements, using which it is possible to represent formally and process all kinds of information from any subject domain, including logical statements, programs and metastructures of any complexity.
SC-code features:
As result:
Semantic and syntax compatibility of knowledge presented in SC-code
Why you should choose us?
The IS Systems allows your company to find meaning in its data and improve the quality of business decisions. On a common platform, IT users and business users can work together to create a data-driven organization:
Enterprise security and scalability to meet your standards of reliability, confidentiality and compliance
System workflows help teams collaborate
Enterprise security and scalability to meet your standards of reliability, confidentiality and compliance
With IS, you rely on reliable data and develop new ideas
1. Identification of all company-related data
First of all, identifying all the data necessary to determine the significant value for the business, we create basic individualized structures that allow the system to expand independently in accordance with its specifications and integrate increasingly complex data. Thus, you use the system in full.
2. Creating a common data language
Consolidate data across all sites by applying a single definition to ensure that users build on the same basis
3. The balance between access and privacy
Our system sets priorities and simplifies approval, use, and retention policies to give analysts access to everything but the right data
4. Develop confidence in the quality of your data
Any analysis will give valid statements only if the data is reliable and full transparency and origin of the data is ensured. This is exactly the basis of the system. Agents, as business intelligence tools, provide powerful analytic capabilities to help you get the insight you need to gain a competitive advantage. The IS Systems ensures that the required data records are found, whose context and origin can be used, and their accuracy can be trusted
5. Expenses and time optimization during functionality extension
In most cases, increasing the functionality of systems developed using our approach comes down to expanding the knowledge base, which can be carried out automatically or with minimal developer participation. Wherein, the requirement for the competence of such developers is much lower than for the competence of the classical systems developer
History
1995
The foundation of artificial intelligence specialty at BSUIR, Minsk
2003
The foundation of artificial intelligence specialty at BrSTU, Brest
2011
The first OSTIS conference and the first OSTIS technology presentation
2019
The 9th OSTIS conference. The idea of integration the OSTIS with artificial neural networks and other machine learning methods. To implement this idea, the IS Systems was founded
Plans
The OSTIS ecosystem is an unlimitedly expandable group of constantly developing intelligent systems that:
interact with each other, with users of intelligent systems, traditional computer systems for cooperative solutions of complex problems;
constantly maintain a high level of compatibility and mutual understanding in interaction both among themselves and with users
The ecosystem includes:
Semantic Associative Computer
Family of compatible intelligent robotic systems and specialized development tools
Family of compatible intelligent personal services and monitoring systems
Family of compatible knowledge portals
Family of compatible intelligent design automation systems in various fields
Family of compatible intelligent geographic information systems
Family of compatible intelligent learning systems
Our Projects
Our main technology development strategy is the constant use of technology in specific applications. This approach allows us to improve and adjust the direction of technology development.
Applications:
Our Team
Thomas Grunewald
CEO
He holds degrees from the Faculty of Radiophysics and Computer Technology and studied Economics and Comparative Law at the University of Mannheim. Over the past 25 years, he has been involved in the founding and development of numerous companies in Eastern Europe. Member of BAAI(Belarusian public association of specialists in the field of artificial intelligence).
Vladimir Golenkov
Chief Scientific Officer (C.S.O.)
Doctor of Computer sciences, professor. Chairman of the Board of BAAI.
Founder of the Department of Intelligent Information Technologies and the specialty "Artificial Intelligence" at BSUIR. Member of the HTP expert council. He conducts research in the field of semantic technologies for the design of intelligent systems, knowledge bases. Leading specialist in the Republic of Belarus in the field of semantic technologies.
Founder of the Department of Intelligent Information Technologies and the specialty "Artificial Intelligence" at BSUIR. Member of the HTP expert council. He conducts research in the field of semantic technologies for the design of intelligent systems, knowledge bases. Leading specialist in the Republic of Belarus in the field of semantic technologies.
Vladimir Golovko
Chief Scientific Officer (C.S.O.)
Doctor of Computer sciences, professor. Board member of BAAI. Founder of the specialty "Artificial Intelligence" at BSTU. He conducts research in the field of artificial neural networks, information security, mobile robots. Leading specialist in the Republic of Belarus in the field of neural network technologies.
Natalia Guliakina
Scientific Officer
PhD in Physico-mathematical sciences, Associate Professor. Board member of BAAI. She conducts research in the field of semantic technologies for the design of intelligent learning systems.
Daniil Shunkevich
Scientific Officer
PhD in Computer sciences. Member of BAAI. He conducts research in the field of knowledge processing in intelligent systems, design of intelligent problem solvers, multi-agent systems.
Mikhail Kovalev
Lead Developer
Master of Computer sciences. Member of BAAI. He conducts research in the field of integration of artificial neural networks and knowledge bases.
Software engineer with 4+ years of experience in commercial programming.
Software engineer with 4+ years of experience in commercial programming.
Our Partners
Contact Us
Phone: +375 17 236 77 36
Mail: info@semantic.by
Minsk, Surganova street, 48a, 220013
Mail: info@semantic.by
Minsk, Surganova street, 48a, 220013
