Computer Tools for Linguistic Research
- The discipline is aimed at students' acquiring knowledge about current computer tools and resources used by linguists in research in the field of corpus, applied and computer linguistics, as well as practical skills in the use of these tools. Computer tools studied within the discipline include concordancers, corpus managers, programs for automatic corpus creation, lemmatizers, stemmers, morphological analyzers and automatic text markup, regular expressions, and Python programming language tools for processing text data.
- Familiar with corpora of the Russian language
- Familiar with the main stages of corpus preprocessing, able to build a corpus (manually and automatically)
- Has an idea of Cipf's law, able to visualize syntax trees, use regular expressions, works with web interfaces of popular corpora, able to make corpora based on the web and explore ready corpora in AntConc
- Has an idea of the periods of development of corpus linguistics, familiar with the main corpus of English
- Understands the basic concepts of corpus linguistics, knows types and properties of corpora, able to obtain concordance. Understands the idea of using the web as a corpus, familiar with the criticism of corpus linguistics
- The student writes technical documentation
- The student is able to correctly label data
- The student is able to analyze data using modern computer tools
- The student is able to write dialogue scripts for chatbots, as well as put them into practice
- The student is able to work in a team and distribute the load among team members
- Acquiring technical writing skills
- Acquiring data labeling skills
- Acquiring data analytics skills
- Acquiring developer-linguist skills
- Acquiring project manager skills
- Control on the block "corpus studies"
- Control on the block "scraping research"
- 2022/2023 4th module0.2 * Exam + 0.4 * Control on the block "scraping research" + 0.4 * Control on the block "corpus studies"
- Dipanjan Sarkar. (2019). Text Analytics with Python : A Practitioner’s Guide to Natural Language Processing: Vol. Second edition. Apress.
- Perkins, J. Python Text Processing with NLTK 2.0 Cookbook: Use Python NLTK Suite of Libraries to Maximize Your Natural Language Processing Capabilities [Электронный ресурс] / Jacob Perkins; DB ebrary. – Birmingham: Packt Publishing Ltd, 2010. – 336 p.
- Fundamentals of project management, Heagney, J., 2012
- Joseph Heagney. (2016). Fundamentals of Project Management: Vol. Fifth edition. AMACOM.
- Грудева Е.В. - Корпусная лингвистика: учебное пособие - Издательство "ФЛИНТА" - 2017 - ISBN: 978-5-9765-1497-3 - Текст электронный // ЭБС ЛАНЬ - URL: https://e.lanbook.com/book/106859