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The article discusses the concept and principles of building unified information space and presents a scheme for its formation. The article considers formation of unified information space using a specialized information computer system, which is actually a hardware and software basis for supporting...
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| author | Dodonov, Alexander Mukhin, Vadym Zavgorodnii, Valerii Kornaga, Yaroslav Zavgorodnya, Anna |
| author_facet | Dodonov, Alexander Mukhin, Vadym Zavgorodnii, Valerii Kornaga, Yaroslav Zavgorodnya, Anna |
| author_sort | Dodonov, Alexander |
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| datestamp_date | 2021-07-13T11:01:37Z |
| description | The article discusses the concept and principles of building unified information space and presents a scheme for its formation. The article considers formation of unified information space using a specialized information computer system, which is actually a hardware and software basis for supporting unified information space. The stages of information object identification in unified information space are considered. The article suggests a method for finding missing features of an incoming object by implementing the information objects interaction with each other within unified information space. |
| doi_str_mv | 10.20535/SRIT.2308-8893.2021.1.03 |
| first_indexed | 2025-07-17T10:27:14Z |
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A. Dodonov, V. Mukhin, V. Zavgorodnii, Ya. Kornaga, A. Zavgorodnya, 2021
34 ISSN 1681–6048 System Research & Information Technologies, 2021, № 1
TIДC
ПРОБЛЕМНО І ФУНКЦІОНАЛЬНО
ОРІЄНТОВАНІ КОМП’ЮТЕРНІ СИСТЕМИ
ТА МЕРЕЖІ
UDC 004.021
DOI: 10.20535/SRIT.2308-8893.2021.1.03
METHOD OF SEARCHING FOR INFORMATION OBJECTS
IN UNIFIED INFORMATION SPACE
A. DODONOV, V. MUKHIN, V. ZAVGORODNII, Ya. KORNAGA,
A. ZAVGORODNYA
Abstract. The article discusses the concept and principles of building unified infor-
mation space and presents a scheme for its formation. The article considers forma-
tion of unified information space using a specialized information computer system,
which is actually a hardware and software basis for supporting unified information
space. The stages of information object identification in unified information space
are considered. The article suggests a method for finding missing features of an in-
coming object by implementing the information objects interaction with each other
within unified information space.
Keywords: unified information space, information object, signs, object identifica-
tion, search method.
INTRODUCTION
Unified information space is an information model of a complex subject area. It
includes information objects, connections between them, environment of the
space and processes accompanying creation of unified information space [1–5].
Unified information space is formed as a result of processing information
about an object, received from various sources.
Here is the contradiction, which is as follows: in order to obtain information
features of objects, the heterogeneous data sources there are used, and these
sources are characterized by varying degrees of accuracy and different formats for
data presenting. At the same time, for the formation of unified information space,
the unification of data obtained from heterogeneous sources is required. The
implementation of a converting mechanism for such formats also is required. So,
the contradiction arises between the heterogeneous nature of sensors for
collecting features of objects and the requirement for a unified data presentation.
In this case, the same object, the parameters of which are obtained from different
sensors, must be uniquely identified anyway.
In the process of forming unified information space, an information
computer system collects information from various data sources presented in
different forms and / or formats, while the processing of incoming data can be
carried out by heterogeneous computer systems [6–8].
To form unified information space, it is required to implement a unified data
entry, store data in uniform formats and exchange information between all infor-
Method of searching for information objects in unified information space
Системні дослідження та інформаційні технології, 2021, № 1 35
mation objects [5, 9, 10]. An information object is a mathematical description of
an initial object by its main parameters. It can be represented as a tuple of pa-
rameters of a real object, and all values of the parameters are determined by the
characteristics of the real object.
Information about objects in unified information space changes dynamically
[11–12].
Creation of unified information space is intended to provide a unified
description of information objects for all users, so that all users of unified
information space perceive the same information object in the same way. This
characteristic is the main feature of unified information space [1, 2].
Thus, unified information space is a complex of tools that support the unity
of presentation, processing and interpretation of information about information
objects. Creation of unified information space is aimed to provide access to
general information without limiting the place and time [13–19].
The information computer system, on the basis of which unified information
space is formed, performs the following main functions:
transformation of information about objects and formation of unified in-
formation space;
providing users with information about objects.
The goal of the research is to consider the concept and principles of
building unified information space and present a scheme for its formation using
a specialized information computer system; describe the stages of identifying an
information object in unified information space; propose a method for finding
missing features of an incoming object.
SCHEME OF UNIFIED INFORMATION SPACE FORMATION
Fig. 1 shows a general scheme for unified information space formation. An impor-
tant task of unified information space is to transform the input information in such a
way that each information object in unified information space is presented uniquely.
Fig. 1. General scheme of unified information space
IOk
Oi
Uniform information space
Object Sensors
Users
A. Dodonov, V. Mukhin, V. Zavgorodnii, Ya. Kornaga, A. Zavgorodnya
ISSN 1681–6048 System Research & Information Technologies, 2021, № 1 36
In unified information space, the attributes of information objects must be
defined in a single format and their number must be the same. Information objects
should also be perceived unambiguously by users of unified information space. In
fact, the input information in unified information space is heterogeneous in its
presentation.
The task of internal mechanisms of an information computer system is to
transform heterogeneous information coming in different formats and from
different sources into a single set of information object attributes, by which uni-
fied information space users can uniquely identify an information object.
STAGES OF INFORMATION OBJECT IDENTIFICATION IN UNIFIED
INFORMATION SPACE
Identification of an information object in unified information space makes it pos-
sible to unambiguously define it by the corresponding features. To identify ob-
jects, an identification method can be used which is based on a step-by-step anal-
ysis of the characteristics of an object using requests to the object in order to
provide an opportunity to make decisions about its identification.
As it shows Fig.1 the external sources of information for unified information
space generally represent objects mO,,O,O 21 in different ways, where m is the
number of objects operated by unified information space. Information about such
objects is received as a set of feature values by reading them using sensors.
Also here is presented the users of unified information space, who’s goal is
to get some information about the objects there.
There are many information objects kIO,,OI,IO 21 , each of which has a
set of features nPPP ,,, 21 , where k is number of information objects, and n is
number of an information object features, i.e., kIO ( nPPP ,,, 21 ).
In this case, it is considered that the same maximum number of features is
set for each information object. Still the number of features for each specific ob-
ject may be less than the maximum — some features may be absent (correspond
to the NONE value), i. e. this object may simply not have this feature.
In unified information space each kOI information object is different, that
is, there are no two absolutely identical information objects:
kIOOI,OIIO 321 .
Therefore, unified information space should work as a kind of reference sys-
tem. For this you need to go through several stages:
1. To form unified information space. It will consist of a set of information
objects, each of which is characterized by a set of features. Such information ob-
jects will differ from each other, that is, they will be unique. Information objects
have connections, so they interact with each other. A connection is understood as
the presence of parameters of another information object in the certain object,
which are obtained as a result of their interaction with each other. Connections
between information objects correspond to the “interaction trajectory”, which is
determined by the pre-history of the of objects interactions with each other.
Method of searching for information objects in unified information space
Системні дослідження та інформаційні технології, 2021, № 1 37
Unified information space is constantly being updated and trained. Forma-
tion of unified information space is the procedure of its training, that is, recogni-
tion of incoming objects without reference to a specific object.
2. Read the characteristics of the incoming object using sensors, which are
a kind of meters. But it happens that sensors may not read some signs of informa-
tion objects, for example, there will be no access, there will be no information
(corresponds to the NULL value).
3. Classification (recognition) of an object. The system receives an object
mO with a set of features, the sensors should read their values, and unified infor-
mation space should unambiguously answer the question of whether there is an
information object in a unified information space with such feature values, or a
new information object will be formed.
METHOD OF SEARCHING FOR MISSING FEATURES IN THE
INFORMATION OBJECT
Information objects have a local feature memory. When a unique identification of
an incoming object occurs, the values of its parameters are added to the memory
of corresponding attributes of the information object. Then, from a set of values
of each information object attribute, statistical characteristics that describe this
attribute are determined — the mathematical expectation M and the variance D ,
and the more input objects are identified by unified information space, the more
accurate they become.
Method of searching for missing features in an information object:
1. Formation of the objects interaction history. Information objects store his-
tory of interactions with each other and an information object can answer the
question whether it interacted with another information object before, and if so,
whether the trajectory of its interaction contains the needed feature. If a given in-
formation object does not have an answer to this question, then it refers to other
information objects of unified information space.
2. Comparison on the basis of features. An object iO with a set of parame-
ters ( nPPP ,,, 21 ) comes to the input. If the value of each parameter falls within
the permissible range of values for the corresponding attribute of a certain infor-
mation object ( DMPDM i ), then unified information space uniquely
identifies the incoming object, that is, ki IOO .
3. Search for missing features. To search for missing features, an informa-
tion object interacts with every other information object from unified information
space. For this, a feature search will be used. This search is based on the trajec-
tory of the objects interaction, and their combination allows gradually narrow the
search area for the missing parameters of the objects. And so on, until all the
missing features are filled in so that unified information space can uniquely iden-
tify the object iO .
4. Clarification (recognition) of missing features. If there are not enough
signs, then it is necessary to turn to other information objects of unified informa-
tion space and request the necessary missing features based on the trajectory of
information objects interaction. For this, it is necessary that each information
object retains the trajectory of interaction, i.e. it actually has a kind of global
A. Dodonov, V. Mukhin, V. Zavgorodnii, Ya. Kornaga, A. Zavgorodnya
ISSN 1681–6048 System Research & Information Technologies, 2021, № 1 38
memory. With such unified information space formation, all trajectories of all
information objects interaction are placed in a single data warehouse.
5. The result is displaying the found object, group of objects or establishing
the fact that the analyzed object is new.
In brief, the method is the next: the identification of an information object is
made according to certain external or internal characteristics of an information
object, taking into account the interaction of an information object in a unified
information space. To support these actions, each information object is supplied
with a set of features that characterize the object to a certain extent. Due to this,
the procedure for identifying an information object is reduced to a simple
comparison of the characteristics of the information object with the characteristics
of the incoming object. If the parameters of an information object in a necessary
and sufficient degree coincide with the parameters of the incoming real object,
then this object is considered as has been identified.
ORGANIZATION AND CONDUCTING EXPERIMENTAL RESEARCH
We will analyze efficiency of incoming objects search in unified information space.
For the experiments, unified information space of 20,000 information objects
was formed.
The percentage of missing parameters in information objects (NONE) was
6%. After that, a single information space is rebuilt by eliminating duplicate in-
formation objects. A series of 20 experiments each was carried out, at certain
probabilities (25, 20, 15, 10 and 5%, respectively) that the parameter would not be
read by the sensors (NULL).
Experiment 1. Let’s consider the case when each of 20,000 information objects
is described by 7 parameters. Below is a snippet of 10 information objects (Table 1).
T a b l e 1 . Fragment of 10 information objects from unified information space
P
IO
Р1 Р 2 Р 3 Р 4 Р 5 Р 6 Р 7
IO1 4 ± 0,5 3 ± 0,9 6 ± 0,7 7 ± 0,1 6 ± 0,9 9 ± 0,4 11 ± 0,6
IO2 5 ± 0,1 6 ± 0,6 6 ± 0,9 7 ± 0,4 6 ± 0,6 6 ± 0,1 9 ± 0,2
IO3 1 ± 0,3 6 ± 0,9 3 ± 0,2 5 ± 0,2 NONE 10 ± 0,4 8 ± 0,4
IO4 1 ± 0,7 6 ± 0,7 7 ± 0,3 6 ± 0,4 6 ± 0,5 NONE 10 ± 0,8
IO5 4 ± 0,4 6 ± 0,6 4 ± 0,4 7 ± 0,2 8 ± 0,3 6 ± 0,5 8 ± 0,4
IO6 5 ± 0,4 4 ± 0,8 6 ± 0,4 4 ± 0,5 5 ± 0,7 8 ± 0,8 9 ± 0,7
IO7 2 ± 0,3 3 ± 0,6 7 ± 0,4 NONE 7 ± 0,6 9 ± 0,7 8 ± 0,6
IO8 3 ± 0,4 5 ± 0,5 5 ± 0,4 6 ± 0,2 9 ± 0,6 NONE 7 ± 0,5
IO9 2 ± 0,9 2 ± 0,5 3 ± 0,2 4 ± 0,9 8 ± 0,2 6 ± 0,5 11 ± 0,2
IO10 1 ± 0,2 6 ± 0,7 6 ± 0,4 8 ± 0,7 9 ± 0,3 8 ± 0,3 11 ± 0,5
In this case, the interval length for each parameter was 5 units, for example,
for the parameter 1P [1; 6).
The following variants of the results were obtained:
1. When the sensors read all the values of the parameters of the incoming ob-
ject and its unique identification has occurred:
New object:
5,8 6,5 6,2 4,8 9,6 9,5 9,7
Method of searching for information objects in unified information space
Системні дослідження та інформаційні технології, 2021, № 1 39
Search object:
IO 06106 5 ± 0,3 6 ± 0,4 6 ± 0,7 4 ± 0,9 9 ± 0,4 9 ± 0,6 9 ± 0,2
2. When the sensors read all the values of the incoming object parameters
and its identification did not occur, there was no information object in unified in-
formation space that would describe this incoming object:
New object:
4,9 3,3 4,5 7,9 5,2 6,5 11,7
Object is absent!
In this case, this incoming object becomes a new information object and can
be added to unified information space.
3. When the sensors did not read the values of all parameters of the incoming
object (NULL), but due to the interaction of information objects with each other
in unified information space, a unique identification of the incoming object took
place:
New object:
5,2 Null 6,4 6,3 5,5 10,1 9,9
Search object:
IO 02727 5 ± 0,1 4 ± 0,4 6 ± 0,5 6 ± 0,8 5 ± 0,6 10 ± 0,8 9 ± 0,2
IO 13394 5 ± 0,6 2 ± 0,2 6 ± 0,8 6 ± 0,4 5 ± 0,2 10 ± 0,1 9 ± 0,9
IO 14824 5 ± 0,1 5 ± 0,3 6 ± 0,9 6 ± 0,9 5 ± 0,4 10 ± 0,2 9 ± 0,4
ReCreateObject:
5,2 4,1 6,4 6,3 5,5 10,1 9,9
Search object:
IO 02727 5 ± 0,1 4 ± 0,4 6 ± 0,5 6 ± 0,8 5 ± 0,6 10 ± 0,8 9 ± 0,2
4. When the sensors did not read the values of all parameters of the incoming
object and, despite the interaction of information objects with each other in uni-
fied information space, identification of the incoming object did not occur:
New object:
2,1 4,5 3,5 Null 9,6 9,2 Null
Search object:
IO 08264 2 ± 0,3 4 ± 0,2 3 ± 0,7 None 9 ± 0,6 9 ± 0,7 10 ± 0,4
IO 08473 2 ± 0,6 4 ± 0,6 3 ± 0,3 6 ± 0,8 9 ± 0,2 9 ± 0,5 8 ± 0,4
IO 16500 2 ± 0,9 4 ± 0,7 3 ± 0,1 8 ± 0,4 9 ± 0,4 9 ± 0,6 8 ± 0,4
ReCreateObject:
2,1 4,5 3,5 Null 9,6 9,2 8,5
Search object:
IO 08473 2 ± 0,6 4 ± 0,6 3 ± 0,3 6 ± 0,8 9 ± 0,2 9 ± 0,5 8 ± 0,4
IO 16500 2 ± 0,9 4 ± 0,7 3 ± 0,1 8 ± 0,4 9 ± 0,4 9 ± 0,6 8 ± 0,4
ReCreateObject:
2,1 4,5 3,5 5,1 9,6 9,2 8,5
Object absent!
5. When the sensors did not count values of one or several parameters and,
after the interaction of information objects with each other in unified information
space, it was found that this object does not have this feature (NONE).
New object:
2,7 4,7 4,1 8,3 5,5 Null 7,6
A. Dodonov, V. Mukhin, V. Zavgorodnii, Ya. Kornaga, A. Zavgorodnya
ISSN 1681–6048 System Research & Information Technologies, 2021, № 1 40
Search object:
IO 12602 2 ± 0,5 4 ± 0,4 4 ± 0,3 8 ± 0,7 5 ± 0,8 10 ± 0,9 7 ± 0,8
ReCreateObject:
2,7 4,7 4,1 8,3 5,5 Null 7,6
ReCreateObject:
2,7 4,7 4,1 8,3 5,5 Null 7,6
ReCreateObject:
2,7 4,7 4,1 8,3 5,5 None 7,6
Object absent!
Generalization of the experiments results made it possible to conclude about
search efficiency of incoming objects in unified information space with 7 parame-
ters and an interval length of 5 units, which is presented in Table 2.
T a b l e 2 . Search efficiency of incoming objects in unified information space
with 7 parameters and an interval length of 5 units
Probability that the parameter will not be
read by sensors (NULL),%
Probability of an incoming object
identification,%
5 20
10 10
15 25
20 15
25 15
Table 2 shows that search efficiency of incoming objects in unified informa-
tion space with 7 parameters and an interval length of 5 units is low.
Therefore, it was decided to reduce number of parameters that describe the
object, and conduct similar experiments with 4, 5 and 6 parameters with the same
initial data. The results of the experiments are presented in Table 3.
T a b l e 3 . Search efficiency of incoming objects in unified information space
with 4, 5 and 6 parameters and an interval length of 5 units
Probability of an incoming object identification
depending on the number of parameters, %
Probability that the parameter
will not be read by sensors
(NULL), %
4 5 6
5 100 100 65
10 100 100 45
15 100 90 85
20 100 100 75
25 100 100 50
Based on the data in Tables 2 and 3, a graph was built for comparing search
efficiency of incoming objects in unified information space with 4, 5, 6 and 7 pa-
rameters and an interval length of 5 units (Fig. 2).
Method of searching for information objects in unified information space
Системні дослідження та інформаційні технології, 2021, № 1 41
From Fig. 2, we can conclude that search efficiency of incoming objects in
unified information space with an interval length of 5 units was on average: with
4 parameters — 100%, with 5 parameters — 98%, with 6 parameters — 64% and
with 7 parameters — 17%.
Accordingly, a decrease in the number of parameters leads to a sharp in-
crease in search efficiency of incoming objects in unified information space.
Experiment 2. When analyzing the conclusions of experiment 1, it was de-
cided to change the lengths of the values intervals of the parameters of the in-
coming objects in unified information space with a constant value of parame-
ters number.
Let us consider the case when each of 20,000 information objects is de-
scribed by 7 parameters, but with different interval lengths of parameter values of
3, 4, and 5 units. The results of the experiments are presented in table 4.
T a b l e 4 . Search efficiency of incoming objects in unified information space
with 7 parameters and an interval length of 3, 4 and 5 units
Probability of an incoming object identification
depending on the interval length, %
Probability that the parameter
will not be read by sensors
(NULL),% 3 4 5
5 100 75 20
10 100 40 10
15 95 50 25
20 100 65 15
25 100 50 15
Based on the data in Table 4, a graph was built for comparing search effi-
ciency of incoming objects in unified information space with 7 parameters and an
interval length of 3, 4, and 5 units (Fig. 3).
From Fig. 3, we can conclude that search efficiency of incoming objects in
unified information space with 7 parameters on average was: with an interval
length of 3 units — 99%, 4 units — 56%, 5 units — 17%.
54
7
6
Fig. 2. Comparative graph of search efficiency of incoming objects in unified informa-
tion space with 4, 5, 6 and 7 parameters and an interval length of 5 units
A. Dodonov, V. Mukhin, V. Zavgorodnii, Ya. Kornaga, A. Zavgorodnya
ISSN 1681–6048 System Research & Information Technologies, 2021, № 1 42
Accordingly, an increase in the interval length leads to a sharp decrease in
search efficiency of incoming objects in unified information space.
Experiment 3. When analyzing the conclusions of experiment 2, it was de-
cided to conduct similar experiments with a small interval length, but a larger
number of incoming objects parameters in unified information space.
Let us consider the case when each of 20,000 information objects is de-
scribed by 8, 9, and 10 parameters with a length of parameter value intervals be-
ing 3 units. The results of the experiments are presented in Table 5.
T a b l e 5 . Efficiency of searching for incoming objects in unified information
space with 8, 9 and 10 parameters with a length of parameter value intervals
of 3 units
Probability of an incoming object identification
depending on the number of parameters,%
Probability that the parameter
will not be read by sensors
(NULL),% 7 8 9 10
5 100 85 35 25
10 100 80 40 5
15 95 90 35 10
20 100 90 45 25
25 100 95 40 15
Based on the data in Tables 4 and 5, a graph was constructed for comparing
searching efficiency of incoming objects in unified information space with 7, 8, 9
and 10 parameters and the length of the parameter values interval of 3 units (Fig. 4).
Fig. 3. Comparative graph of search efficiency of incoming objects in unified informa-
tion space with 7 parameters and an interval length of 3, 4 and 5 units
5
3
4
Method of searching for information objects in unified information space
Системні дослідження та інформаційні технології, 2021, № 1 43
From Fig. 4, we can conclude that search efficiency of incoming objects in
unified information space with length of parameter value interval of 3 units on
average was: with 7 parameters — 99%, with 8 parameters — 88%, with 9 pa-
rameters — 39%, and with 10 parameters — 16%.
Accordingly, search efficiency of incoming objects in unified information
space is the highest with 7 and 8 parameters and with length of the parameter
values interval of 3 units.
CONCLUSIONS
The article discusses formation of unified information space using a specialized
information computer system, which is actually a hardware and software basis for
supporting a single information space.
The stages of information object identification in unified information space
are considered. The article proposes the method of searching for missing features
of the incoming object by implementing information objects interaction with each
other within unified information space.
The experiments described in the article make it possible to evaluate search
efficiency of incoming objects in unified information space when the number of
incoming parameters and interval of their values change. The experiments have
shown that the identification probability depends significantly on the number of
parameters of the original object, as well as on the length of the intervals de-
scribing values of the object parameters themselves. At the same time, with an
increase in number of original object parameters and the interval length of object
parameters, search efficiency of incoming objects in unified information space
significantly decreases.
Thus, a promising direction of research is the development of specialized
methods for identifying objects in unified information space, which will improve
object identification efficiency in conditions of an increase in number of the orig-
inal object parameters and the interval length of object parameters.
Fig. 4. Comparative graph of search efficiency of incoming objects in unified information
space with 7, 8, 9 and 10 parameters and length of the parameter value interval of 3 units
8
7
10
9
A. Dodonov, V. Mukhin, V. Zavgorodnii, Ya. Kornaga, A. Zavgorodnya
ISSN 1681–6048 System Research & Information Technologies, 2021, № 1 44
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vol. 9, no. 6, pp. 225–261, 2015. doi:10.5539/mas.v9n6p255
13. Z. Hu, V. Mukhin, Ya. Kornaga, O. Herasymenko, and Y. Mostoviy, “The Analyti-
cal Model for Distributed Computer System Parameters Control Based on Multi-
factoring Estimations”, Journal of Network and Systems Management, no. 27 (2),
pp. 351–365, 2019.
14. V. Mukhin, Y. Kornaga, V. Zavgorodnii, A. Zavgorodnya, O. Herasymenko, and
O. Mukhin, “Social Risk Assessment Mechanism Based on the Neural Networks”,
International Conference on Advanced Trends in Information Theory (ATIT–2019),
18–20 Dec. 2019, pp. 179–182.
15. H. Zhenbing, V. Mukhin, Ya. Kornaga, and O. Herasymenko, “Resource Manage-
ment in a Distributed Computer System with Allowance for the Level of Trust to
Computational Components”, Cybernetics and Systems Analysis, no. 53 (2),
pp. 312–322, 2017.
16. V. Mukhin, Ya. Kornaga, Y. Mostovyi, and Y. Bazaka, “A Model For Events Moni-
toring Heterogeneous Distributed Databases Based on Vector-matrix Operations”,
Method of searching for information objects in unified information space
Системні дослідження та інформаційні технології, 2021, № 1 45
The Far East Journal of Electronics and Communications, vol. 16, issue 3,
pp. 645–656, 2016.
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нии”, Перспективы науки и образования, № 4, c. 30–38, 2013.
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ления сложной организационно-технической системой. Информационный
аспект. Москва: МаксПресс, 2010, 228 с.
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ности единого информационного пространства”, Вестн. С.-Петерб. ун-та
МВД, № 2, c. 150–154, 2013.
Received 21.01.2021
INFORMATION ON THE ARTICLE
Alexander G. Dodonov, Institute of Problems of Information Registration of the National
Academy of Sciences of Ukraine, Ukraine, e-mail: dodonovua@gmail.com
Vadym E. Mukhin, ORCID: 0000-0002-1206-9131, National Technical University of
Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Ukraine, e-mail: v.mukhin@kpi.ua
Valerii V. Zavgorodnii, State University of Infrastructure and Technology, Ukraine,
e-mail: zavgorodniivalerii@gmail.com
Yaroslav I. Kornaga, National Technical University of Ukraine “Igor Sikorsky Kyiv
Polytechnic Institute”, Ukraine, e-mail: slovyan_k@ukr.net
Anna A. Zavgorodnya, State University of Infrastructure and Technology, Ukraine,
e-mail: annzavgorodnya@gmail.com
МЕТОД ПОИСКА ИНФОРМАЦИОННЫХ ОБЪЕКТОВ В ЕДИНОМ
ИНФОРМАЦИОННОМ ПРОСТРАНСТВЕ / А.Г. Додонов, В.Е. Мухин,
В.В. Завгородний, Я.И. Корнага, А.А. Завгородняя
Аннотация. Рассмотрены понятие и принципы построения единого информа-
ционного пространства и представлена схема его формирования. Рассмотрено
формирование единого информационного пространства с использованием
специализированной информационной компьютерной системы, которая фак-
тически является аппаратно-программным базисом для поддержки единого
информационного пространства, а также этапы идентификации информацион-
ного объекта в едином информационном пространстве. Предложен метод по-
иска недостающих признаков входящего объекта путем реализации взаимо-
действия информационных объектов между собой внутри единого
информационного пространства.
Ключевые слова: единое информационное пространство, информационный
объект, признаки, идентификация объекта, метод поиска.
МЕТОД ПОШУКУ ІНФОРМАЦІЙНИХ ОБ’ЄКТІВ В ЄДИНОМУ
ІНФОРМАЦІЙНОМУ ПРОСТОРІ / О.Г. Додонов, В.Є. Мухін, В.В. Завгородній,
Я.І. Корнага, Г.А. Завгородня
Анотація. Розглянуто поняття і принципи побудови єдиного інформаційного
простору і подано схему його формування. Розглянуто формування єдиного
інформаційного простору з використанням спеціалізованої інформаційної
комп’ютерної системи, яка фактично є апаратно-програмним базисом для під-
тримання єдиного інформаційного простору, а також етапи ідентифікації ін-
формаційного об’єкта в єдиному інформаційному просторі. Запропоновано
метод пошуку відсутніх ознак вхідного об’єкта шляхом реалізації взаємодії
інформаційних об’єктів між собою всередині єдиного інформаційного простору.
Ключові слова: єдиний інформаційний простір, інформаційний об’єкт, озна-
ки, ідентифікація об’єкта, метод пошуку.
A. Dodonov, V. Mukhin, V. Zavgorodnii, Ya. Kornaga, A. Zavgorodnya
ISSN 1681–6048 System Research & Information Technologies, 2021, № 1 46
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O. Mukhin, “Social Risk Assessment Mechanism Based on the Neural Networks”, Inter-
national Conference on Advanced Trends in Information Theory (ATIT–2019), 18–20
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a Distributed Computer System with Allowance for the Level of Trust to Computational
Components”, Cybernetics and Systems Analysis, no. 53 (2), pp. 312–322, 2017.
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|
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| institution | System research and information technologies |
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| language | English |
| last_indexed | 2025-07-17T10:27:14Z |
| publishDate | 2021 |
| publisher | The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" |
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| spelling | journaliasakpiua-article-2365272021-07-13T11:01:37Z Method of searching for information objects in unified information space Метод поиска информационных объектов в едином информационном пространстве Метод пошуку інформаційних об’єктів в єдиному інформаційному просторі Dodonov, Alexander Mukhin, Vadym Zavgorodnii, Valerii Kornaga, Yaroslav Zavgorodnya, Anna єдиний інформаційний простір інформаційний об’єкт ознаки ідентифікація об’єкта метод пошуку unified information space information object signs object identification search method единое информационное пространство информационный объект признаки идентификация объекта метод поиска The article discusses the concept and principles of building unified information space and presents a scheme for its formation. The article considers formation of unified information space using a specialized information computer system, which is actually a hardware and software basis for supporting unified information space. The stages of information object identification in unified information space are considered. The article suggests a method for finding missing features of an incoming object by implementing the information objects interaction with each other within unified information space. Рассмотрены понятие и принципы построения единого информационного пространства и представлена схема его формирования. Рассмотрено формирование единого информационного пространства с использованием специализированной информационной компьютерной системы, которая фактически является аппаратно-программным базисом для поддержки единого информационного пространства, а также этапы идентификации информационного объекта в едином информационном пространстве. Предложен метод поиска недостающих признаков входящего объекта путем реализации взаимодействия информационных объектов между собой внутри единого информационного пространства. Розглянуто поняття і принципи побудови єдиного інформаційного простору і подано схему його формування. Розглянуто формування єдиного інформаційного простору з використанням спеціалізованої інформаційної комп’ютерної системи, яка фактично є апаратно-програмним базисом для підтримання єдиного інформаційного простору, а також етапи ідентифікації інформаційного об’єкта в єдиному інформаційному просторі. Запропоновано метод пошуку відсутніх ознак вхідного об’єкта шляхом реалізації взаємодії інформаційних об’єктів між собою всередині єдиного інформаційного простору. The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" 2021-07-13 Article Article application/pdf https://journal.iasa.kpi.ua/article/view/236527 10.20535/SRIT.2308-8893.2021.1.03 System research and information technologies; No. 1 (2021); 34-46 Системные исследования и информационные технологии; № 1 (2021); 34-46 Системні дослідження та інформаційні технології; № 1 (2021); 34-46 2308-8893 1681-6048 en https://journal.iasa.kpi.ua/article/view/236527/235080 |
| spellingShingle | єдиний інформаційний простір інформаційний об’єкт ознаки ідентифікація об’єкта метод пошуку Dodonov, Alexander Mukhin, Vadym Zavgorodnii, Valerii Kornaga, Yaroslav Zavgorodnya, Anna Метод пошуку інформаційних об’єктів в єдиному інформаційному просторі |
| title | Метод пошуку інформаційних об’єктів в єдиному інформаційному просторі |
| title_alt | Method of searching for information objects in unified information space Метод поиска информационных объектов в едином информационном пространстве |
| title_full | Метод пошуку інформаційних об’єктів в єдиному інформаційному просторі |
| title_fullStr | Метод пошуку інформаційних об’єктів в єдиному інформаційному просторі |
| title_full_unstemmed | Метод пошуку інформаційних об’єктів в єдиному інформаційному просторі |
| title_short | Метод пошуку інформаційних об’єктів в єдиному інформаційному просторі |
| title_sort | метод пошуку інформаційних об’єктів в єдиному інформаційному просторі |
| topic | єдиний інформаційний простір інформаційний об’єкт ознаки ідентифікація об’єкта метод пошуку |
| topic_facet | єдиний інформаційний простір інформаційний об’єкт ознаки ідентифікація об’єкта метод пошуку unified information space information object signs object identification search method единое информационное пространство информационный объект признаки идентификация объекта метод поиска |
| url | https://journal.iasa.kpi.ua/article/view/236527 |
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