TYPE OF COURSE UNIT	Elective Course
LEVEL OF COURSE UNIT	Doctorate Of Science
YEAR OF STUDY	-
SEMESTER	-
NUMBER OF ECTS CREDITS ALLOCATED	10
NAME OF LECTURER(S)	-
LEARNING OUTCOMES OF THE COURSE UNIT	At the end of this course, the students; 1) Know natural language analysis techniques with rule based and statistical methods. 2) Understand uncertainty problem analysis in Natural Language Processing analysis and know elimination techniques. 3) Know existing research and application techniques by literature review. 4) Know syntactic and semantic Natural Language Processing methods. 5) Know importance and features of collections in Natural Language Processing 6) Understand Language models. 7) Understand Zipf rules and N-grams. 8) Know the methods of labeling word type and application area. 9) Know word parsing and derivation methods. 10) Know determination of phrases. 11) Know machine translation methods.
MODE OF DELIVERY	Face to face
PRE-REQUISITES OF THE COURSE	No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT	None
COURSE DEFINITION	Parsing Algorithms; Morphological Analysis; Morphological Ambiguity; Applying Finite-State Methods for Language Processing Tasks; Machine Translation and Information Retrieval
COURSE CONTENTS	WEEK TOPICS 1st Week Parsing Algorithms; 2nd Week Parsing Algorithms; 3rd Week Morphological Analysis; 4th Week Morphological Analysis; 5th Week Morphological Analysis; 6th Week Morphological Ambiguity; 7th Week Morphological Ambiguity; 8th Week Mid-term 9th Week Applying Finite-State Methods for Language Processing Tasks; 10th Week Applying Finite-State Methods for Language Processing Tasks; 11th Week Applying Finite-State Methods for Language Processing Tasks; 12th Week Machine Translation and Information Retrieval 13th Week Machine Translation and Information Retrieval 14th Week Machine Translation and Information Retrieval
RECOMENDED OR REQUIRED READING	1. Jurafsky, D. and Martin, J. H. "Speech and Language Processing", Prentice Hall, (2000) 2. Manning, C. D. and H. Schütze "Foundations of Statistical Natural Language Processing", The MIT Press, (1999) 3. Allen, J. "Natural Language Understanding", The Benjamins/Cummings Publishing Company Inc., (1994)
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS	Lecture,Questions/Answers,Practice,Problem Solving,Project,Report Preparation,Presentation
ASSESSMENT METHODS AND CRITERIA	Quantity Percentage(%) Mid-term 1 30 Assignment 1 10 Project 1 20 Total(%) 60 Contribution of In-term Studies to Overall Grade(%) 60 Contribution of Final Examination to Overall Grade(%) 40 Total(%) 100
ECTS WORKLOAD	Activities Number Hours Workload Midterm exam 1 2 2 Preparation for Quiz Individual or group work 14 11 154 Preparation for Final exam 1 69 69 Course hours 14 3 42 Preparation for Midterm exam 1 44 44 Laboratory (including preparation) Final exam 1 2 2 Homework Total Workload 313 Total Workload / 30 10,43 ECTS Credits of the Course 10
LANGUAGE OF INSTRUCTION	Turkish
WORK PLACEMENT(S)	No