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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS CME 4408 INTRODUCTION TO NATURAL LANGUAGE PROCESSING ELECTIVE 2 2 0 6

Offered By

Computer Engineering

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSISTANT PROFESSOR ÖZLEM AKTAŞ

Offered to

Computer Engineering

Course Objective

The aim of this course is to provide the students to learn modelling natural languages.

Learning Outcomes of the Course Unit

1   Define morphological and statistical analysis 2   Differentiate the difference between working on small files and big files. 3   Collect big enough data to model the language 4   Construct a preliminary model for a natural language 5   Explain how ngram analysis is used in different areas

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Course Overview, Explaining Grading System and Assignments 2 Introduction. Knowledge in Speech and Language Processing. Ambiguity. Brief History. 3 Regular Expressions 4 Finite State Automata 5 Recognition as Search. Regular Languages ans FSAs. 6 Inflectional and Derivational Morphology 7 Entropy. Finite-State Morphological Parsing. Minimum Edit Distance(MED). 8 Midterm 9 The Porter Stemmer and Human Morphological Processing 10 Working with large Corpus 11 N-Grams 12 Smoothing 13 Zipf's Law and Mandelbrot Constants 14 General Overview

Recomended or Required Reading

Speech and Language Processing,Daniel Jurafsky,James H. Martin, ,Prentice Hall,0131873210 ,New Jersey,2008

Planned Learning Activities and Teaching Methods

By using presentation tools the course is taught in class. By giving programming assignments and project, all the students are expected to learn the modelling natural languages.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 ASG ASSIGNMENT 3 PRJ PROJECT 4 FIN FINAL EXAM 5 FCG FINAL COURSE GRADE MTE * 0.20 + ASG * 0.20 + PRJ * 0.20 + FIN * 0.40 6 BUT Bütünleme Notu 7 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.20 + ASG * 0.20 + PRJ * 0.20 + RST * 0.40 *** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Learning outcome 1 will be asked in exams. Learning outcomes 2,3,4 and 5 will be supported by assignments.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

email: ozlem@cs.deu.edu.tr

Office Hours

Thursday 10:30-12:00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 13 2 26 Tutorials 13 2 26 Preparations before/after weekly lectures 13 2 26 Preparation for midterm exam 1 8 8 Preparation for final exam 1 16 16 Preparing assignments 8 3 24 Final 1 2 2 Midterm 1 2 2 Project Assignment 8 1 8 TOTAL WORKLOAD (hours) 138

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 PO.10 LO.1 5 3 3 LO.2 3 LO.3 4 5 4 4 5 LO.4 3 3 LO.5 3 3 5 5 3