Natural Language Processing (ΠΛ6): Διαφορά μεταξύ των αναθεωρήσεων
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(6 ενδιάμεσες αναθεωρήσεις από τον ίδιο χρήστη δεν εμφανίζεται) | |||
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[[ | * [[Επεξεργασία Φυσικής Γλώσσας (ΠΛ6)|Ελληνική Έκδοση]] | ||
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=== General === | === General === | ||
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=== Syllabus === | === Syllabus === | ||
* Properties of the Computation Theory Mathematical Models | |||
* Problems classification to solvable and unsolvable | |||
* Solvable Problems Classification | |||
=== Teaching and Learning Methods - Evaluation === | === Teaching and Learning Methods - Evaluation === | ||
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! Delivery | ! Delivery | ||
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Face to face | |||
|- | |- | ||
! Use of Information and Communications Technology | ! Use of Information and Communications Technology | ||
| | | Yes | ||
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! Teaching Methods | ! Teaching Methods | ||
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| 39 | | 39 | ||
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| | | Self study | ||
| | | 78 | ||
|- | |- | ||
| | | Exercises | ||
| | | 70.5 | ||
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| Course total | | Course total | ||
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! Student Performance Evaluation | ! Student Performance Evaluation | ||
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* Final essays (40%) . | |||
* Exercises -questions requiring critical thinking (30%). | |||
* Presentations of related issues (30%). | |||
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Τελευταία αναθεώρηση της 05:17, 16 Ιουνίου 2023
- Ελληνική Έκδοση
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General
School | School of Science |
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Academic Unit | Department of Mathematics |
Level of Studies | Graduate |
Course Code | ΠΛ6 |
Semester | 1 |
Course Title | Natural Language Processing |
Independent Teaching Activities | Lectures (Weekly Teaching Hours: 3, Credits: 7.5) |
Course Type | Specialization |
Prerequisite Courses |
Undergraduate courses in Automata Theory and Formal Languages, Introduction to Natural language Processing. |
Language of Instruction and Examinations |
Greek |
Is the Course Offered to Erasmus Students | Yes (in English) |
Course Website (URL) | See eCourse, the Learning Management System maintained by the University of Ioannina. |
Learning Outcomes
Learning outcomes |
The goal of this course is the deeper understanding of Natural Language Processing which concern to:
as well as the introduction of students to critical thinking and research process. During the course a detailed examination of the above topics is done. After completing the course the student can handle theoretical documentation of problems and solving exercises, which are related to:
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General Competences |
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Syllabus
- Properties of the Computation Theory Mathematical Models
- Problems classification to solvable and unsolvable
- Solvable Problems Classification
Teaching and Learning Methods - Evaluation
Delivery |
Face to face | ||||||||||
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Use of Information and Communications Technology | Yes | ||||||||||
Teaching Methods |
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Student Performance Evaluation |
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Attached Bibliography
- 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.