CMP711 Natural Language Processing

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Semester	Fall 2023
Instructor	Prof. Dr. İlyas Çiçekli Email:  ilyas@cs.hacettepe.edu.tr
Class Hours	Wednesday 9:30-12:30 Classroom: Seminer Hall

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Text Book

1. Daniel Jurafsky, and James H. Martin, "Speech and Language Processing", Third Edition, Prentice Hall, 2018.

Other References

1. Christopher D. Manning, and Hinrich Schutze, "Foundations of Statistical Natural Language Processing", The MIT Press, 1999.

2. Bird, Steven, Edward Loper and Ewan Klein, “Natural Language Processing with Python”, O’Reilly Media Inc., 2009.

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Grading

Project	40%
Final Exam	40%
Homework	20%

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Project

Each student will do a survey in an advanced topic in NLP field, and a computational work as a project. You should read at least 2-3 major papers in that field, and prepare a professionally written paper (in the format of a conference or journal paper) for your project. At the end of semester, you will return your paper together with the copies of the major papers that you read and you will make a demo of your project.

Possible Project Topics You should write one page document for your project proposal and it should include your project title and the references to major papers related with your project and the description of your project.

Project Proposal Date: 25 October 2023

You should submit your project proposal before due date.

Midway Project Report: 6 December 2023

At the middle of the semester, you will submit your midway project report. This means that you should finish some of your project work before the midway point.

Project Demo Date: 17 January 2024 (or before) (HARD DEADLINE)

You have to make a demo of your project to me on these dates. You may give all your source files and executable files on your demo day.

Due Date for Final Project Report: 17 January 2024 (or before) (HARD DEADLINE)) -Your project is NOT complete until you give all of the followings. Bring all of them on your demo day or send them as a single zipped file.

1. A soft copy of your final project report. ( IEEEFormat )

2. All of your source code files, executable files and all files related with your project (including sample input-output files and a readme file how to execute your project).

3. Soft copies of the papers in your survey.

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Course Outline:

Subject	Related chapters in 3rd edition of textbook
Introduction/Overview of NLP	Ch. 1
Regular Expressions, Text Normalization, Edit Distance	Ch. 2
N-gram Language Models, Spelling Correction	Ch. 3 & Appendix B
Text Classification: Naive Bayes and Logistic Regression	Ch. 4 and Ch. 5
Vector Semantics	Ch. 6
Morphological Processing	Ch. 3 from 2^nd edition of the book
Part-of-Speech Tagging	Ch. 8
Context-Free Grammars and Syntactic Parsing	Ch. 10 and Ch. 11
Statistical Parsing	Ch. 12
Dependency Parsing	Ch. 13
Representation of Sentence Meaning	Ch. 14
Semantic Analysis and Computational Semantics	Ch. 15 and Ch. 16
Information Extraction	Ch. 17
Machine Translation, Question Answering, Dialog Systems and Chatbots	Ch. 22, Ch.23, Ch. 25

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Lecture Notes:

• lec01-introduction.pdf
• lec02-BasicTextProcessing.pdf
• lec02-MinimumEditDistance.pdf
• lec03-LanguageModels.pdf
• lec04-SpellingCorrection.pdf
• lec05-TextClassificationNaiveBayes.pdf
• lec06-LogisticRegression.pdf
• lec07-VectorSemantics.pdf
• lec08-VS_Word2Vec.pdf
• lec09-MorphologicalProcessing.pdf
• lec10-PartOfSpeechTagging.pdf
• lec11-SyntacticParsing.pdf
• lec12-SyntacticParsingFeatures.pdf
• lec13-StatisticalParsing.pdf
• lec14-SentenceMeaning.pdf

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Announcements:

· We will use the LISANSUSTU system ( https://lisansustu.hacettepe.edu.tr/ ) for all course announcements. You will use that system in order to submit your project and homework documents. You will find your grades in that system.

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