Intelligent Semantic Systems

integration of machine learning approaches, such as artificial neural networks models with semantic models on the universal formal basis

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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
Ensuring the reliability of
information obtained from
various sources
Use of distibuted ledger
technologies (DLT)
Automation of the process of
analyzing the quality of
stored information
Impossibility of intentional or
accidental distortion of
information
Use of distibuted ledger
technologies (DLT)
Fixation of all system
changes in its knowledge base
Automation of the process of
analyzing the quality of stored
information
Errors count reduction
No duplication of information
Automation of the process of
analyzing the quality of
stored information
Reducing the costs of updating
and expanding information
resources
Low laboriousness of stored
information correction,
including knowledge bases
tructure correction
Ease of stored information
updating, including
automation of this process
Company information is used
much more efficiently
Search for the necessary
information for all types of
users is simplified
The ability to store
meta-information at any
level
The ability to automatically
identify the most important
information fragments
The ability to structure a
knowledge base by
anunlimited number of
attributes
No duplication of information
Each user receives only the
information that he
currently needs
The ability to store
meta-information at any
level
The ability to automatically
identify the most important
information fragments
The ability to structure a
knowledge base by anunlimited
number of attributes
Automation of the business
processes
The ability to store
meta-information at any
level
No duplication of information
Automation of the process of
analyzing the quality of stored
information
Ease of stored information
updating, including
automationof this process
Employees work load
optimization
The ability to store
meta-information at any
level
The ability to automatically
identify the most important
information fragments
No duplication of information
Automation of the process of
analyzing the quality of
stored information
Low laboriousness of stored
information correction,
including knowledge base
structure correction
Ease of stored information
updating, including
automation of this process
Reducing the costs of updating
and expanding information
resources
The ability to structure
aknowledge base by an unlimited number of attributes
No duplication of information
Automation of the process of
analyzing the quality of stored
information
Low laboriousness of stored
information correction,
including knowledge base
structure correction
Ease of stored information
updating, including
automation of this process
Reduced costs for the study of
the system by users (both
employees and customers)
The ability to ask questions
about the system itself
Possibility of dialogue in a
language close to natural
System can be unlimitedly
improved and
intellectualized
Expanding the variety of
questions, which may
beasked to the system
Low laboriousness of the
system functionality
expanding
The possibility of step-by-step
intellectualization without any
restrictions
Low laboriousness of system
adaptation to new tasks
System maintenance and
development costs are
significantly reduced
No duplication of information
Automation of the process
of analyzing the quality of
stored information
Low laboriousness of stored
information correction,
including knowledge base
structure correction
Ease of stored information
updating, including
automationof this process
Low laboriousness of the
system functionality
expanding
The possibility of step-by-step
intellectualization without any
restrictions
Low laboriousness of system
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 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

            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.

            Main directions of technology application within OSTIS ecosystem:

            Complex technology for semantically compatible intelligent systems development
            Family of intelligent systems standards
            Semantic Associative Computer
            Complex technology for natural language interfaces and natural language understanding systems development
            Complex technology for image understanding systems development
            Family of compatible intelligent robotic systems and correspondent 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 in context of Industry 4.0
            Family of compatible intelligent geographic information systems
            Family of compatible intelligent education systems

            Technology applications currently presented in open-source form:

            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.


            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
            System Architect
            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 Software Engineer
            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.

            Our Partners

            Contact us
            +375 17 236 77 36
            info@semantic.by
            Minsk, Surhanava street, 48a, 220013