INTRODUCTION TO COMPUTATIONAL LINGUISTICS

Course Information
TitleΕΙΣΑΓΩΓΗ ΣΤΗΝ ΥΠΟΛΟΓΙΣΤΙΚΗ ΓΛΩΣΣΟΛΟΓΙΑ / INTRODUCTION TO COMPUTATIONAL LINGUISTICS
CodeΓΛΩ397
FacultyPhilosophy
SchoolPhilology
Cycle / Level1st / Undergraduate
Teaching PeriodWinter/Spring
CommonYes
StatusActive
Course ID280006581

Programme of Study: UPS School of Philology 2015

Registered students: 11
OrientationAttendance TypeSemesterYearECTS
Glōssologías Mandatory Elective CoursesWinter/Spring-6
Class Information
Academic Year2017 – 2018
Class PeriodWinter
Faculty Instructors
Total Hours39
Class ID
600104545
Course Type 2016-2020
  • Background
Course Type 2011-2015
General Foundation
Mode of Delivery
  • Face to face
Digital Course Content
Language of Instruction
  • Greek (Instruction, Examination)
Learning Outcomes
• Learning of the basic principles and problems in Computational Linguistics. • Familiarizing with basic concepts and strategies of algorithmic problem solving. • Learning of basic data structures in programming with Python. • Connection between theory and praxis by modeling and implementing grammatical phenomena through programming. • Capability of implementing small scale computational projects of natural language processing. • Learning markup/annotation strategies with XML.
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Make decisions
  • Work in teams
Course Content (Syllabus)
A) Basic notions of formal languages B) COmputer memory, variables, data types: string manipulation, lists and methods in python C) Phrase Structure Grammars ( Context-free grammars) D) Control structures (while, for and if) I E) Phrase Structure Grammars ( Context-sensitive grammars) F) Control structures (while, for and if) II and functions in python I G) Functions in Python II H) Finite State Automata and morphology I I) Finite State Automata and morphology II J) Data type "dict" and creation of a small scale greek grammar in python K) Corpus Processing with Python and various custom software I L) Corpus Processing with Python and various custom software II M) Corpus Annotation in XML I N) M) Corpus Annotation in XML II
Keywords
Formal Languages, Chomsky Hierarchy, Finite State Automata, Phrase-structure Grammars, Corpora, Python, XML
Educational Material Types
  • Notes
  • Slide presentations
  • Scientific papers
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Laboratory Teaching
  • Use of ICT in Communication with Students
Description
The course is taking place in a computer lab. All theoretical concepts are explicated on the basis of programming examples in Python and XML.
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures281✓✓✓
Laboratory Work843✓✓✓
Written assigments281✓✓
Exams281✓✓
Total1686
Student Assessment
Student Assessment methods
  • Written Exam with Short Answer Questions (Summative)
  • Written Assignment (Formative)
  • Written Exam with Problem Solving (Formative, Summative)
  • Labortatory Assignment (Formative)
Bibliography
Course Bibliography (Eudoxus)
Fromkin V., R. Rodman & N. Hyams. (2008). Εισαγωγή στη μελέτη της γλώσσας (μτφρ. Γ. Ξυδόπουλος, Φ. Παπαδοπούλου, Έ. Βάζου & Α. Τσαγγαλίδης). Αθήνα: Εκδόσεις Πατάκη. Τάντος, Α., Μαρκαντωνάτου, Σ., Αναστασιάδη-Συμεωνίδη, Ά., Κυριακοπούλου, Π., 2015. Υπολογιστική γλωσσολογία. [ηλεκτρ. βιβλ.] Αθήνα:Σύνδεσμος Ελληνικών Ακαδημαϊκών Βιβλιοθηκών. Διαθέσιμο στο: http://hdl.handle.net/11419/2205
Additional bibliography for study
Jurafsky, D. & J. H. Martin. (2009). Speech and Language Processing: An Introduction to Natural Language Processing, Speech Recognition, and Computational Linguistics. 2nd edition. Prentice-Hall. Partee B., A. Ter Meulen & R. E. Wall (1990). Mathematical Methods in Linguistics. Dordrecht/Boston/London: Kluwer Academic Publishers.
Last Update
05-02-2020