Introduction to Natural Languages Processing (MAE845): Διαφορά μεταξύ των αναθεωρήσεων
Από Wiki Τμήματος Μαθηματικών
Χωρίς σύνοψη επεξεργασίας |
|||
Γραμμή 120: | Γραμμή 120: | ||
=== Attached Bibliography === | === Attached Bibliography === | ||
See [https://service.eudoxus.gr/public/departments#20 Eudoxus]. Additionally: | |||
* Mitkov Ruslan, The Oxford Handbook of Computational Linguistics. ISBN 0-19-823882 | * Mitkov Ruslan, The Oxford Handbook of Computational Linguistics. ISBN 0-19-823882 | ||
* Jurafsky Daniel & Martin H. James, Speech and Language Processing - An Introduction to Ntural Language Proocessing, Computational Linguistics and Speech Recognition. ISBN 0-13-095069-6 | * Jurafsky Daniel & Martin H. James, Speech and Language Processing - An Introduction to Ntural Language Proocessing, Computational Linguistics and Speech Recognition. ISBN 0-13-095069-6 |
Αναθεώρηση της 17:19, 23 Ιουλίου 2022
Undergraduate Courses Outlines - Department of Mathematics
General
School |
School of Science |
---|---|
Academic Unit |
Department of Mathematics |
Level of Studies |
Undergraduate |
Course Code |
MAE845 |
Semester |
8 |
Course Title |
Introduction to Natural Language Processing |
Independent Teaching Activities |
Lectures (Weekly Teaching Hours: 3, Credits: 6) |
Course Type |
Special Background |
Prerequisite Courses | - |
Language of Instruction and Examinations |
Greek |
Is the Course Offered to Erasmus Students |
Yes (in English) |
Course Website (URL) | http://nlampp-lab.uoi.gr/lab/ |
Learning Outcomes
Learning outcomes |
The goal of this course is the deeper understanding of Natural Language Processing (NLP). During the course a detailed examination of the following topics are done:
After completing the course the student can handle:
which related to NLP different topics. |
---|---|
General Competences |
|
Syllabus
- A historical retrospection of Language Technology evolution
- The goal of NLP and its Applications
- The NLP levels. Language Processors such as recognition machines, transducers, parsers and generators
- The language as a rule based system. Language Understanding as process
- NLP Resources for parsing, such as Data Base, Knowledge Base, Data Structure, Algorithms and Expert Systems
- Fundamental parsing strategies concerning context free grammars.
- Fundamental Methods of Computational Morphology, Computational Semantics and NLP. Implementations-Applications
Teaching and Learning Methods - Evaluation
Delivery |
Face to face | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Use of Information and Communications Technology |
Yes , Use of Natural Language and Mathematical Problems Processing Laboratory | ||||||||||
Teaching Methods |
| ||||||||||
Student Performance Evaluation |
Final test |
Attached Bibliography
See Eudoxus. Additionally:
- Mitkov Ruslan, The Oxford Handbook of Computational Linguistics. ISBN 0-19-823882
- Jurafsky Daniel & Martin H. James, Speech and Language Processing - An Introduction to Ntural Language Proocessing, Computational Linguistics and Speech Recognition. ISBN 0-13-095069-6
- Allen James, Natural Language Understanding. ISBN 0-8053-0334-0,
- Natural Language Generation ed. by Gerard Kempen. ISBN 90-247-3558-0
- Professor's Notes.