Natural Language Processing (ΠΛ6): Διαφορά μεταξύ των αναθεωρήσεων
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! Learning outcomes | ! Learning outcomes | ||
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The goal of this course is the deeper understanding of Natural Language Processing which concern to: | |||
* the NL linguistics data formalization | |||
* the codification of the NL syntax, morphology and semantics structure rules | |||
* the parsing and generation algorithms of NL sentences | |||
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: | |||
* definition and design of syntactic structure or phrase structure grammars as well as algorithms and syntactic analysis technics. | |||
* formalization of morphological rules, design data bases and expert systems as well as algorithms and morphological analysis technics. | |||
* formalization of semantic rules, design data bases and expert systems as well as algorithms and semantic analysis technics. | |||
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! General Competences | ! General Competences | ||
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* Independent work | |||
* Bibliographic search | |||
* Effective selection and Design of the required machine and language. | |||
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Αναθεώρηση της 19:54, 10 Νοεμβρίου 2022
Graduate Courses Outlines - Department of Mathematics
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
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Teaching and Learning Methods - Evaluation
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Use of Information and Communications Technology |
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Student Performance Evaluation |
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