Master
2021/2022
Semantic Technologies
Type:
Elective course (Information Analytics in Enterprise Management )
Area of studies:
Business Informatics
Delivered by:
Department of Information Technologies in Business
Where:
Faculty of Economics
When:
1 year, 3, 4 module
Mode of studies:
distance learning
Online hours:
18
Open to:
students of one campus
Master’s programme:
Information Analytics in Enterprise Management
Language:
English
ECTS credits:
7
Contact hours:
52
Course Syllabus
Abstract
The present program of educational discipline establishes requirements to educational results and learning outcomes of the student and determines the content and types of training sessions and reporting. The program is intended for the teachers conducting discipline "Semantic Technologies", educational assistants and students of a direction of preparation 38.04.05 Business informatics, studying under the educational program "Business Analytics".
Learning Objectives
- Development of students' skills in applying modern technologies of intellectual data processing on the basis of their semantic interpretation
Expected Learning Outcomes
- conducts professional, including research activities in the international environment
- The student is able to use information retrieval thesauruses and ontologies to process information.
- The student is able to apply a logical model of knowledge representation.
- The student is able to apply semantic networks to represent knowledge.
- The student is able to apply the production model of knowledge representation.
- The student is able to use frames to represent knowledge.
- The student is ready for oral and written communication both in Russian and foreign languages in order to achieve goals within professional and scientific environment
- The student knows and is able to use natural language processing technologies and tools.
- The student knows and is able to use natural language processing technology.
- The student knows and is able to use Semantic Web technologies.
Course Contents
- Theme 1: Models of knowledge presentation, overview
- Theme 2: Logical model of knowledge representation
- Theme 3: Production model of knowledge representation
- Theme 4: Frames for the presentation of knowledge
- Theme 5: Semantic networks for knowledge representation
- Theme 6: Ontology and thesauruses
- Theme 7. Computer linguistics
- Theme 8: Stages of text analysis
- Theme 9: Tools for developing automated text processing applications
- Theme 10. Introduction to Semantic Web technology
- Theme 11. Basic technologies of Semantic Web
- Theme 12. Agents in Semantic Web
Assessment Elements
- Lab work 1
- Lab work 2
- Lab work 3
- Lab work 4
- Lab work 5
- Lab work 6
- Lab work 7 (independent work)
- ExamОценка за экзамен выставляется как среднее арифметическое по 7-ми выполненным лабораторным работам. An exam assessment is arithmetic average of 7 completed laboratory work.
- Evaluation for taking online courses
- Lab work 7 (independent work)
Interim Assessment
- 2021/2022 4th module0.075 * Lab work 6 + 0.075 * Lab work 7 (independent work) + 0.075 * Lab work 2 + 0.075 * Lab work 5 + 0.4 * Exam + 0.075 * Lab work 4 + 0.075 * Lab work 3 + 0.075 * Evaluation for taking online courses + 0.075 * Lab work 1
Bibliography
Recommended Core Bibliography
- Загорулько Ю. А., Загорулько Г. Б. - ИСКУССТВЕННЫЙ ИНТЕЛЛЕКТ. ИНЖЕНЕРИЯ ЗНАНИЙ. Учебное пособие для вузов - М.:Издательство Юрайт - 2019 - 93с. - ISBN: 978-5-534-07198-6 - Текст электронный // ЭБС ЮРАЙТ - URL: https://urait.ru/book/iskusstvennyy-intellekt-inzheneriya-znaniy-442134
Recommended Additional Bibliography
- Назаров Д. М., Конышева Л. К. - ИНТЕЛЛЕКТУАЛЬНЫЕ СИСТЕМЫ: ОСНОВЫ ТЕОРИИ НЕЧЕТКИХ МНОЖЕСТВ 3-е изд., испр. и доп. Учебное пособие для академического бакалавриата - М.:Издательство Юрайт - 2019 - 186с. - ISBN: 978-5-534-07496-3 - Текст электронный // ЭБС ЮРАЙТ - URL: https://urait.ru/book/intellektualnye-sistemy-osnovy-teorii-nechetkih-mnozhestv-423214
- Семантический веб / Г. Антониоу, П. Грос, в. Ф. Хармелен, Р. Хоекстра ; перевод с английского Т. Шульга. — Москва : ДМК Пресс, 2016. — 240 с. — ISBN 978-5-97060-333-8. — Текст : электронный // Лань : электронно-библиотечная система. — URL: https://e.lanbook.com/book/69963 (дата обращения: 00.00.0000). — Режим доступа: для авториз. пользователей.