UIINP31 Natural Language Processing II

Faculty of Philosophy and Science in Opava
Summer 2024
Extent and Intensity
2/1/0. 5 credit(s). Type of Completion: zk (examination).
Teacher(s)
Mgr. Daniel Valenta, Ph.D. (lecturer)
Mgr. Daniel Valenta, Ph.D. (seminar tutor)
Guaranteed by
Mgr. Daniel Valenta, Ph.D.
Institute of Computer Science – Faculty of Philosophy and Science in Opava
Timetable
Mon 8:55–10:30 B3b
  • Timetable of Seminar Groups:
UIINP31/A: Mon 10:35–11:20 B3b, D. Valenta
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The main topic of this course is the automation of the process of translation and correction of the text (in succession of the course Natural Language Processing I). In this course, students will get familiar with most serious problems of the computer understanding of the content of the text in natural language and the principles of solving these problems.
Learning outcomes
Students will be able to:
- describe the issue of machine translation and text correction
- identify and describe the problems of the computer understanding of the content of the text in natural language
Syllabus
  • 1. Automatic referencing.
  • 2. Machine translation. A word-for-word method, its inherent limitations, and further development to so-called direct translation systems (eg: SYSTRAN). 2nd generation methods: interlingual and with transfer separate from analysis and synthesis. What structures can generally be used to describe the linguistic meaning.
  • 3. What should be the general strategy for analysis, transfer, and synthesis, what tools can contribute to its implementation. Translation as general knowledge manipulation.
  • 4. Possibilities of partial translation automation.
  • 5. Automated proofreading of texts. Levels in terms of depth of analysis (spelling and mechanical, grammar, style). Generally possible goals, types of errors, possible solutions, and major limitations.
Literature
    required literature
  • Laboratoř zpracování přirozeného jazyka. Stručný terminologický slovník počítačové lingvistiky [online]. [cit. 2014-04-29]. Dostupné z: http://nlp.fi.muni.cz/cs/terminologie
    recommended literature
  • UHRÍN, Tibor. Přirozený jazyk a umělý jazyk. Inflow: information journal [online]. 2008, roč. 1, č. 11 [cit. 2013-04-28]. Dostupný z: http://www.inflow.cz/prirozeny-jazyk-umely-jazyk. ISSN 1802-9736
  • Strossa. Počítačové zpracování přirozeného jazyka. Praha, 2011. ISBN 978-80-245-1777-3. info
Teaching methods
Interactive lectures, tutorials
Assessment methods
Credit: Active participation at the tutorials min. 75%, pass the written test.
Exam: written
Language of instruction
Czech
Further Comments
Study Materials
The course can also be completed outside the examination period.
The course is also listed under the following terms Summer 2020, Summer 2021, Summer 2022, Summer 2023.
  • Enrolment Statistics (recent)
  • Permalink: https://is.slu.cz/course/fpf/summer2024/UIINP31