NATURAL LANGUAGE PROCESSING

BİL621

Course Code: BİL621
Semester: -
Theory+Practice: 3 + 0
ECTS: 10

Course Type

Elective Course

Course Level

Doctorate Of Science

Year of Study

Semester

ECTS

Name of Lecturer(s)

Learning Outcomes

At the end of this course, the students;

Know natural language analysis techniques with rule based and statistical methods.
Understand uncertainty problem analysis in Natural Language Processing analysis and know elimination techniques.
Know existing research and application techniques by literature review.
Know syntactic and semantic Natural Language Processing methods.
Know importance and features of collections in Natural Language Processing
Understand Language models.
Understand Zipf rules and N-grams.
Know the methods of labeling word type and application area.
Know word parsing and derivation methods.
Know determination of phrases.
Know machine translation methods.

Mode of Delivery

Face to face

Prerequisites

Recommended Optional Programme Components

None

Course Description

Parsing Algorithms; Morphological Analysis; Morphological Ambiguity; Applying Finite-State Methods for Language Processing Tasks; Machine Translation and Information Retrieval

Course Contents

WEEK	TOPICS
1^st Week	Parsing Algorithms;
2^nd Week	Parsing Algorithms;
3^rd Week	Morphological Analysis;
4^th Week	Morphological Analysis;
5^th Week	Morphological Analysis;
6^th Week	Morphological Ambiguity;
7^th Week	Morphological Ambiguity;
8^th Week	Mid-term
9^th Week	Applying Finite-State Methods for Language Processing Tasks;
10^th Week	Applying Finite-State Methods for Language Processing Tasks;
11^th Week	Applying Finite-State Methods for Language Processing Tasks;
12^th Week	Machine Translation and Information Retrieval
13^th Week	Machine Translation and Information Retrieval
14^th Week	Machine Translation and Information Retrieval

Recommended 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 Allocated Based on Student Workload

Activities	Quantity	Duration (Hour)	Total Workload (Hour)
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 Work Load			313
Total Work Load / 30 (h)			10.43
ECTS Credit of the Course			10

Language of Instruction

Turkish

Work Placement(s)

Programme Qualifications / Learning Outcomes

	LO1	LO2	LO3	LO4	LO5	LO6	LO7	LO8	LO9	LO10	LO11
K1	X	X	X	X	X	X	X	X	X	X	X
K2		X	X		X			X		X
K3						X	X	X			X
K4		X	X		X		X	X	X	X
K5	X	X	X			X			X
K6			X		X	X	X	X		X
K7						X	X	X		X
K8	X	X	X	X			X	X		X
K9					X	X
K10		X									X
K11					X	X	X	X
K12	X	X	X	X	X	X	X	X		X