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Information
| Code | YZ007 |
| Name | Advanced Computational Linguistics |
| Term | 2024-2025 Academic Year |
| Term | Fall |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Yüksek Lisans Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | |
| Course Instructor |
1 |
Course Goal / Objective
In this course, the main goal is to define the methods and approaches used in Computational Linguistics.
Course Content
Normalization, Tokenizing, Lemmatization, Parsing, Syntax, N-Gram analysis, Features and Analysis, Part of Speech Tagging, Treebank, Semantic analysis, Morphological and Semantic Ambiguity, Lexical Similarity, Semantic Similarity, Dialogue Systems, Question Answering, Machine Translation, Keyword Extraction, Document Summarization, Paraphrasing, Ontology Mapping
Course Precondition
none
Resources
Daniel Jurafsky and James H. Martin, Speech and language processing an introduction to natural language processing, computational linguistics, and speech, 2000.
Notes
Articles
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Knows basic NLP terms |
| LO02 | Does basic text operations |
| LO03 | Knows semantical and morphological analysis and ambiguation |
| LO04 | Knows which analyzes to do with NLP |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Beceriler - Bilişsel, Uygulamalı | To be able to access information broadly and deeply by conducting scientific research in the field, to be able to evaluate, interpret and apply the information. | |
| PLO02 | Bilgi - Kuramsal, Olgusal | Has a comprehensive knowledge of current techniques and methods applied in engineering and their limitations. | 4 |
| PLO03 | Beceriler - Bilişsel, Uygulamalı | To be able to use uncertain, limited or incomplete data to complete and apply knowledge using scientific methods; to be able to use knowledge from different disciplines together. | 4 |
| PLO04 | Bilgi - Kuramsal, Olgusal | Is aware of new and emerging practices of the profession, examines and learns them when needed. | 4 |
| PLO05 | Beceriler - Bilişsel, Uygulamalı | Defines and formulates problems related to the field, develops methods to solve them and applies innovative methods in solutions. | |
| PLO06 | Beceriler - Bilişsel, Uygulamalı | Develops new and/or original ideas and methods; designs complex systems or processes and develops innovative/alternative solutions in their designs. | 4 |
| PLO07 | Beceriler - Bilişsel, Uygulamalı | Designs and implements theoretical, experimental and modeling-based research; examines and solves complex problems encountered in this process. | |
| PLO08 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | To be able to work effectively in disciplinary and multidisciplinary teams, to lead such teams and to develop solution approaches in complex situations; to be able to work independently and take responsibility. | |
| PLO09 | Bilgi - Kuramsal, Olgusal | To be able to communicate orally and in writing in a foreign language at least at the B2 level of the European Language Portfolio. | |
| PLO10 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | To be able to communicate the process and results of his/her studies systematically and clearly in written or oral form in national and international environments in or outside the field. | |
| PLO11 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Knows the social, environmental, health, safety, legal, project management and business life practices of engineering applications and is aware of the constraints these impose on engineering applications. | |
| PLO12 | Bilgi - Kuramsal, Olgusal | Observes social, scientific and ethical values in the stages of data collection, interpretation and announcement and in all professional activities. |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Introduction to NLP: Concepts and terms | Preliminary research on the subject | Öğretim Yöntemleri: Anlatım |
| 2 | Normalization, Tokenizing, Lemmatization, Parsing | Preliminary research on the subject | Öğretim Yöntemleri: Anlatım |
| 3 | Syntax, N-Gram analysis | Preliminary research on the subject | Öğretim Yöntemleri: Anlatım |
| 4 | Corpus: Features and Analysis | Preliminary research on the subject | Öğretim Yöntemleri: Anlatım |
| 5 | Part of Speech Tagging, Treebank | Preliminary research on the subject | Öğretim Yöntemleri: Anlatım |
| 6 | Semantic analysis (probabilistic methods) | Preliminary research on the subject | Öğretim Yöntemleri: Anlatım |
| 7 | Morphological and Semantic Ambiguity | Preliminary research on the subject | Öğretim Yöntemleri: Anlatım |
| 8 | Mid-Term Exam | Preparation for the exam | Ölçme Yöntemleri: Yazılı Sınav |
| 9 | Lexical Similarity | Preliminary research on the subject | Öğretim Yöntemleri: Anlatım |
| 10 | Semantic Similarity | Preliminary research on the subject | Öğretim Yöntemleri: Anlatım |
| 11 | Dialogue Systems, Question Answering | Preliminary research on the subject | Öğretim Yöntemleri: Anlatım |
| 12 | Machine Translation | Preliminary research on the subject | Öğretim Yöntemleri: Anlatım |
| 13 | Keyword Extraction, Document Summarization | Preliminary research on the subject | Öğretim Yöntemleri: Anlatım |
| 14 | Paraphrasing, Ontology Mapping | Preliminary research on the subject | Öğretim Yöntemleri: Anlatım |
| 15 | New Generation Transformers | Preliminary research on the subject | Öğretim Yöntemleri: Anlatım |
| 16 | Term Exams | Preparation for the exam | Ölçme Yöntemleri: Yazılı Sınav |
| 17 | Term Exams | Preparation for the exam | Ölçme Yöntemleri: Yazılı Sınav |
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 | ||