CEN471 Natural Language Processing

6 ECTS - 3-0 Duration (T+A)- 7. Semester- 3 National Credit

Information

Unit FACULTY OF ENGINEERING
COMPUTER ENGINEERING PR. (ENGLISH)
Code CEN471
Name Natural Language Processing
Term 2020-2021 Academic Year
Semester 7. Semester
Duration (T+A) 3-0 (T-A) (17 Week)
ECTS 6 ECTS
National Credit 3 National Credit
Teaching Language İngilizce
Level Lisans Dersi
Type Normal
Label E Elective
Mode of study Uzaktan Öğretim
Catalog Information Coordinator Prof. Dr. UMUT ORHAN
Course Instructor Prof. Dr. UMUT ORHAN (Güz) (A Group) (Ins. in Charge)


Course Goal / Objective

Learning the methods and approaches used in Natural Language Processing

Course Content

Processing natural languages in computer

Course Precondition

Resources

Notes



Course Learning Outcomes

Order Course Learning Outcomes
LO01 Knows terms of Natural Language Processing
LO02 Knows N-gram analysis
LO03 Knows semantical analsis, use it in disambiguation and similarity measurement
LO04 Knows WordNet
LO05 Knows to prepare and to comment a corpus
LO06 Comments about summarization, question answering and machine translation systems


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal Adequate knowledge of mathematics, science and related engineering disciplines; ability to use theoretical and applied knowledge in these fields in solving complex engineering problems. 5
PLO02 Bilgi - Kuramsal, Olgusal Ability to identify, formulate and solve complex engineering problems; ability to select and apply appropriate analysis and modeling methods for this purpose. 4
PLO03 Bilgi - Kuramsal, Olgusal Ability to design a complex system, process, device or product to meet specific requirements under realistic constraints and conditions; ability to apply modern design methods for this purpose. 3
PLO04 Bilgi - Kuramsal, Olgusal Ability to select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering practice; ability to use information technologies effectively. 4
PLO05 Bilgi - Kuramsal, Olgusal Ability to design and conduct experiments, collect data, analyze and interpret results to investigate complex engineering problems or discipline-specific research topics. 3
PLO06 Bilgi - Kuramsal, Olgusal Ability to work effectively in interdisciplinary and multidisciplinary teams; individual working skills. 4
PLO07 Bilgi - Kuramsal, Olgusal Ability to communicate effectively verbally and in writing; knowledge of at least one foreign language; ability to write effective reports and understand written reports, prepare design and production reports, make effective presentations, and give and receive clear and understandable instructions.
PLO08 Bilgi - Kuramsal, Olgusal Awareness of the necessity of lifelong learning; ability to access information, follow developments in science and technology, and constantly renew oneself.
PLO09 Bilgi - Kuramsal, Olgusal Knowledge of ethical principles, professional and ethical responsibility, and standards used in engineering practice.
PLO10 Bilgi - Kuramsal, Olgusal Knowledge of business practices such as project management, risk management and change management; awareness of entrepreneurship and innovation; knowledge of sustainable development.
PLO11 Bilgi - Kuramsal, Olgusal Knowledge of the effects of engineering practices on health, environment and safety in universal and social dimensions and the problems of the age reflected in the field of engineering; awareness of the legal consequences of engineering solutions.


Week Plan

Week Topic Preparation Methods
1 Introduction to NLP concept and terms Reading related chapter in lecture notes
2 Normalization, Tokenizing, Lemmatization, Parsing Reading related chapter in lecture notes
3 Syntax, N-Gram analysis Reading related chapter in lecture notes
4 Corpus preparing Reading related chapter in lecture notes
5 Part of Speech Tagging, Treebank Reading related chapter in lecture notes
6 Semantic analysis (probabilistic methods) Reading related chapter in lecture notes
7 Morphological and Word Sense Disambiguation Reading related chapter in lecture notes
8 Mid-Term Exam Study to lecture notes and apllications
9 Word and Sentence similarities Reading related chapter in lecture notes
10 Graph based networks: WordNet, Graph based similarity Reading related chapter in lecture notes
11 Dialogue Systems, Question Answering Reading related chapter in lecture notes
12 Machine Translation Reading related chapter in lecture notes
13 Keyword Extraction, Document Summarization Reading related chapter in lecture notes
14 Paraphrasing Reading related chapter in lecture notes
15 Final Review Reading related chapter in lecture notes
16 Term Exams Study to lecture notes and apllications
17 Term Exams Study to lecture notes and apllications


Assessment (Exam) Methods and Criteria

Assessment Type Midterm / Year Impact End of Term / End of Year Impact
1. Midterm Exam 100 40
General Assessment
Midterm / Year Total 100 40
1. Final Exam - 60
Grand Total - 100


Student Workload - ECTS

Works Number Time (Hour) Workload (Hour)
Course Related Works
Class Time (Exam weeks are excluded) 14 3 42
Out of Class Study (Preliminary Work, Practice) 14 5 70
Assesment Related Works
Homeworks, Projects, Others 0 0 0
Mid-term Exams (Written, Oral, etc.) 1 15 15
Final Exam 1 30 30
Total Workload (Hour) 157
Total Workload / 25 (h) 6,28
ECTS 6 ECTS

Update Time: 29.04.2025 12:47