scholarly journals Decision support in the information maintenance of individual education trajectory based on ontological models and distributed RDF-storage

2021 ◽  
Author(s):  
A. Klimova ◽  
N. Yusupova ◽  
O. Smetanina ◽  
A. Kovtunenko
Keyword(s):  
Decision Support ◽  
Business Processes ◽  
Semantic Analysis ◽  
Educational Systems ◽  
Distributed Software ◽  
Educational Trajectories ◽  
Ontological Model ◽  
Special Approach ◽  
Digital Footprints ◽  
Individual Education

The article considers the problem of decision support in the information maintenance of individual education trajectory. The development of algorithms and software for processes automating in educational systems requires a special approach. The use of ontological models makes it possible to unify the description of the elements of educational systems and apply the technology of digital footprints when managing business processes in educational systems. An ontological model for managing educational trajectories is proposed. An algorithm has also been developed to compare competence-based models of curricula using latent-semantic analysis. The proposed models and methods are implemented as a distributed software system using the semantic web approach on the basis of distributed RDF-storage. The effectiveness of the developed algorithms and software solutions is demonstrated by the example of academic mobility in Ufa State Aviation Technical University. Prospects for further research in this area are outlined.

scholarly journals AN ONTOLOGICAL APPROACH TO THE DEVELOPMENT OF A KNOWLEDGE BASE OF A DECISION SUPPORT SYSTEM FOR CHOOSING AN INDIVIDUAL EDUCATIONAL TRAJECTORY

2021 ◽  
pp. 29-34
Author(s):  
О.В. Баюк ◽  
И.О. Лозикова
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Knowledge Base ◽  
Support System ◽  
Subject Area ◽  
Educational Trajectories ◽  
Ontological Approach ◽  
The Subject ◽  
Ontological Modeling ◽  
Ontological Model

В статье рассмотрены актуальные вопросы онтологического моделирования базы знаний интеллектуальной системы поддержки принятия решения (СППР) по выбору индивидуальной образовательной траектории. Цель работы – разработка онтологической модели базы знаний системы поддержки принятия решения для построения индивидуальной образовательной траектории обучающегося. Предметом исследования является онтологическое моделирование процесса построения индивидуальной образовательной траектории. Актуальность работы обусловлена индивидуализацией образовательного процесса, который предлагается осуществлять по индивидуальным образовательным траекториям (ИОТ). При построении ИОТ большая роль отводится самостоятельному выбору и принятию решения обучающимся, где необходимо ясно видеть возможный результат своего выбора. Система построения сценариев выбора ИОТ или Система поддержки принятия решения (СППР, Decision Support System, DSS) является интеллектуальной системой, ядром которой будет база знаний на основе онтологической модели. Представлены методологические и технологические аспекты моделирования онтологии базы знаний предметной области индивидуальных образовательных траекторий, применение современных программных средств и стандартов разработки онтологических моделей. Описан метод и технология онтологического моделирования, представлены основные технологические стандарты и их теоретические основания, а также основные процессы методики проектирования. Дано описание предметной области онтологической модели, подход к построению модели базы знаний индивидуальной образовательной траектории, где сформулированы целевые вопросы данной онтологии для определения её масштаба и компетентности. Представлен последовательный процесс онтологического моделирования знаний описанной предметной области. Разработаны правила логического вывода для проверки компетентности онтологической модели и представлены результаты логических вычислений. Представлен выбор семантических технологий для разработки СППР. В заключение сделаны выводы о преимуществах онтологического подхода к разработке базы знаний системы поддержки принятия решения по выбору индивидуальной образовательной траектории и о программной архитектуре реализации данной системы. The article deals with topical issues of ontological modeling of the knowledge base of the intelligent decision support system (DSS) for the choice of an individual educational trajectory. The purpose of the work is to develop an ontological model of the knowledge base of the decision support system for building an individual educational trajectory of a student. The subject of the research is the ontological modeling of the process of building an individual educational trajectory. The relevance of the work is due to the individualization of the educational process, which is proposed to be carried out according to individual educational trajectories (IOT). When building an IOT, a large role is assigned to the independent choice and decision-making of students, where it is necessary to clearly see the possible result of their choice. The system for constructing IOT selection scenarios or the Decision Support System (DSS, Decision Support System, DSS) is an intelligent system, the core of which will be a knowledge base based on an ontological model. Methodological and technological aspects of modeling the ontology of the knowledge base of the subject area of individual educational trajectories, the use of modern software tools and standards for the development of ontological models are presented. The method and technology of ontological modeling are described, the main technical standards and their theoretical foundations are presented, as well as the main processes of the design methodology. The article describes the subject area of the ontological model, an approach to building a knowledge base model of an individual educational trajectory, where the target questions of this ontology are formulated to determine its scale and competence. A sequential process of ontological modeling of knowledge of the described subject area is presented. The rules of logical inference for checking the competence of the ontological model are developed and the results of logical calculations are presented. The choice of semantic technologies for the development of DSS is presented. In conclusion, conclusions are made about the advantages of the ontological approach to the development of the knowledge base of the decision support system for choosing an individual educational trajectory and about the software architecture of the implementation of this system.

scholarly journals SITUATION AND ONTOLOGICAL DECISION-MAKING METHODOLOGY ON THE EXAMPLE OF BUSINESS PROCESSES OF AN AIRCRAFT ENTERPRISE

2021 ◽  
Vol 21 (1) ◽  
pp. 102-115
Author(s):  
V.V. Antonov ◽  
◽  
K.A. Konev ◽  
V.A. Suvorova ◽  
G.G. Kulikov ◽  
...  
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Business Process ◽  
Behavioral Problems ◽  
Business Processes ◽  
Support Systems ◽  
Aircraft Industry ◽  
Ontological Model

This article proposes an improved methodology for the development of decision support systems, developed on the basis of a situational scheme for solving behavioral problems by a person. The proposed methodology proposes an approach to solving the problem of decision support based on the ontological model of an organization (business process), containing information about typical situations, their features, options (scenarios) of decisions and indicators for choosing these decisions. An intelligent mechanism for “recognition” of the states of typical situations has been developed on the basis of categorization and the use of the obtained hierarchy of their states and features. A general approach to keeping the ontological model up to date is proposed. The examples of the application of the methodology for the enterprise of the aircraft industry are considered.

NBIC-TECHNOLOGIES FOR A DIGITAL ECONOMY

2021 ◽  
Author(s):  
О.Н. МАСЛОВ
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Simulation Modeling ◽  
Information Technologies ◽  
Business Processes ◽  
Digital Economy ◽  
Biological Information ◽  
Role Of Information ◽  
New Formation

Дается обоснование необходимости ускоренного внедрения NBIC-технологий (нанотехнологии, информацион -ные, биологические и когнитивные технологии) в отечественное производство на стадии его перехода к цифровой экономике. Рассматривается проблема формирования системы генерации и реализации инновационных знаний; показана ключевая роль информационных технологий (реинжиниринг бизнес-процессов, имитационное моделирование, системы поддержки реше -ний и др.). Отмечена важность подготовки кадров новой формации, способных использовать достижения NBIC-технологий в интересах современного производства. The paper discusses the need for accelerated implementation of NBIC-technologies (according to the first letters of their names: nanotechnology, biological, information, and cognitive technologies) in domestic production at the stage of its transition to the digital economy. The problem of forming a system for generating and implementing innovative knowledge is considered. The key role of information technologies (business processes reengineering, simulation modeling, decision support systems, etc.) in its solution is shown. The importance of training personnel of a new formation, capable of using the achievements of NBIC-technologies in the interests of modern production, is noted.

scholarly journals AI for augmenting human judgement in Business Processes Management

2021 ◽  
Vol 201 (3) ◽  
pp. 507-518
Author(s):  
Łukasz Osuszek ◽  
Stanisław Stanek
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Decision Support ◽  
Business Processes ◽  
Workflow Management ◽  
Organizational Memory ◽  
Machine Learning Algorithms ◽  
Analytical Models ◽  
Case Based Reasoning ◽  
Historical Case

The paper outlines the recent trends in the evolution of Business Process Management (BPM) – especially the application of AI for decision support. AI has great potential to augment human judgement. Indeed, Machine Learning might be considered as a supplementary and complimentary solution to enhance and support human productivity throughout all aspects of personal and professional life. The idea of merging technologies for organizational learning and workflow management was first put forward by Wargitsch. Herein, completed business cases stored in an organizational memory are used to configure new workflows, while the selection of an appropriate historical case is supported by a case-based reasoning component. This informational environment has been recognized in the world as being effective and has become quite common because of the significant increase in the use of artificial intelligence tools. This article discusses also how automated planning techniques (one of the oldest areas in AI) can be used to enable a new level of automation and processing support. The authors of the article decided to analyse this topic and discuss the scientific state of the art and the application of AI in BPM systems for decision-making support. It should be noted that readily available software exists for the needs of the development of such systems in the field of artificial intelligence. The paper also includes a unique case study with production system of Decision Support, using controlled machine learning algorithms to predictive analytical models.

scholarly journals Intelligent decision support method in a typical situation

2021 ◽  
Vol 11 (1) ◽  
pp. 126-136
Author(s):  
V.V. Antonov ◽  
◽  
K.A. Konev
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Knowledge Base ◽  
Business Process ◽  
Support System ◽  
System Integration ◽  
General Structure ◽  
Typical Situation ◽  
Ontological Model ◽  
Decision Support Method

The article discusses a decision support method using a knowledge base. The relevance of the study of issues related to decision-making in typical situations is shown. In order to increase the effectiveness of management activities, the is-sues of system integration of the regulatory framework, ontological model and knowledge base of the intelligent sub-system of decision support within the framework of the business process are considered. In support of the proposed method, a model has been formed for replenishing the knowledge base both at the structural and analytical levels, which demonstrates the connection between the most important elements of the system: the ontological model, the knowledge base and the normative subsystem. An example of using the proposed scheme is shown. To demonstrate the model of functioning of the decision support system, an algorithm for replenishing the knowledge base is proposed and described. As a conceptual basis for the formal description of the model, operations for working with knowledge are described in the set-theoretic aspect. The principles of adaptation of the ontological model as an information object for linking with the knowledge base are considered. The conceptual diagram of the general structure of the ontological model for making decisions within the framework of the business process as a set of interrelated concepts is proposed and demonstrated. An information model of a specialized database has been developed and presented, serving as a technical basis for building a knowledge base of a decision support system in a typical situation, its main structural el-ements, the principles of their interrelation and an approach to ensuring the consistency of its internal structure are de-scribed.

ALBIS

2013 ◽  
pp. 188-206
Author(s):  
Lerina Aversano ◽  
Carmine Grasso ◽  
Maria Tortorella
Keyword(s):  
Information Retrieval ◽  
Software Maintenance ◽  
Business Processes ◽  
Semantic Analysis ◽  
Software Systems ◽  
Complex Task ◽  
Process Performance ◽  
Definition Of ◽  
Support Software

The evaluation of the alignment level existing between a business process and the supporting software systems is a critical concern for an organization, as the higher the alignment level is, the better the process performance is. Monitoring the alignment implies the characterization of all the items it involves and definition of measures for evaluating it. This is a complex task, and the availability of automatic tools for supporting evaluation and evolution activities may be precious. This chapter presents the ALBIS Environment (Aligning Business Processes and Information Systems), designed to support software maintenance tasks. In particular, the proposed environment allows the modeling and tracing between business and software entities and the measurement of their alignment degree. An information retrieval approach is embedded in ALBIS based on two processing phases including syntactic and semantic analysis. The usefulness of the environment is discussed through two case studies.

Business Intelligence and Data Mining

2013 ◽  
pp. 57-70
Author(s):  
Zsolt T. Kardkovács
Keyword(s):  
Data Mining ◽  
Decision Support ◽  
Strategic Planning ◽  
Decision Support Systems ◽  
Business Intelligence ◽  
Business Processes ◽  
Support Systems ◽  
Decision Makers ◽  
Key Factors ◽  
Short Introduction

Whenever decision makers find out that they want to know more about how the business works and progresses, or why customers do what they do, then data miners are summoned, and business intelligence is to be built or altered. Data mining aims at retrieving valid, interesting, explicable connection between key factors for either operative reporting or supporting strategic planning. While data mining discovers static connections between factors, business intelligence visualizes relevant data for decision makers in order to make them identify fast changes and analyze precisely business states. In this chapter, the authors give a short introduction for data oriented decision support systems with data mining and business intelligence in it. While these techniques are widely used in business processes, there are much more bad practices than good ones. We try to make an attempt to demystify and clear the myths about these technologies, and determine who should and how (not) to use them.

Databased Decision Support for the Design of Business Processes in Manufacturing Companies

2021 ◽  
pp. 565-573
Author(s):  
M. Schopen ◽  
L. Geesmann ◽  
S. Schmitz ◽  
A. Gützlaff ◽  
G. Schuh
Keyword(s):  
Decision Support ◽  
Business Processes ◽  
Manufacturing Companies
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