Natural Language Processing (ΠΛ6): Διαφορά μεταξύ των αναθεωρήσεων

Από Wiki Τμήματος Μαθηματικών
Γραμμή 50: Γραμμή 50:
! Learning outcomes
! Learning outcomes
|
|
ΧΧΧ
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.
|-
|-
! General Competences
! General Competences
|
|
ΧΧΧ
* Independent work
* Bibliographic search
* Effective selection and Design of the required machine and language.
|}
|}



Αναθεώρηση της 19:54, 10 Νοεμβρίου 2022

Graduate Courses Outlines - Department of Mathematics

General

School School of Science
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:

  • 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.
General Competences
  • Independent work
  • Bibliographic search
  • Effective selection and Design of the required machine and language.

Syllabus

ΧΧΧ

Teaching and Learning Methods - Evaluation

Delivery

ΧΧΧ

Use of Information and Communications Technology

ΧΧΧ

Teaching Methods
Activity Semester Workload
Lectures 39
ΧΧΧ 000
ΧΧΧ 000
Course total 187.5
Student Performance Evaluation

ΧΧΧ

Attached Bibliography

Πρότυπο:MAM199-Biblio