CENG463 INTRODUCTION TO NATURAL LANGU. PROCESSING
| Course Code: | 5710463 |
| METU Credit (Theoretical-Laboratory hours/week): | 3 (3.00 - 0.00) |
| ECTS Credit: | 6.0 |
| Department: | Computer Engineering |
| Language of Instruction: | English |
| Level of Study: | Undergraduate |
| Course Coordinator: | Lecturer Dr. AYŞE NUR BİRTÜRK |
| Offered Semester: | Fall or Spring Semesters. |
Course Objectives
To form a basis for Natural Language Processing and Computational Linguistics and preparing the student for an advanced graduate course on computational linguistics. To present applicable linguistic theory by turning theories into practical techniques with emphasis on problems for which there are widely accepted solutions. To familiarize the student with the latest advances in Natural Language Technology and applications using Python and NLTK (Natural Language Toolkit).
Course Content
Introduction to linguistic theory and techniques used in natural language processing (NLP). Template and keyword systems. Declarative and procedural approaches to NL parsing. Phrase Structure. Unification-based grammar. Parsing algorithms. Semantics. Morphology and Lexicon.
Course Learning Outcomes
Understand the basic concepts and terminology in natural language study
Access and use natural language corpora
Recognize the statistical properties of text from raw corpora
Create finite state automata and finite state transducers for morphological analysis of words
Design two level compilers for morphological analysis
Understand sequence classification methods
Apply the supervised training algorithm for HMMs for POS tagging
Calculate probabillities of POS tag sequences
Apply dynamic programming algorithms such as Viterbi to choose the best POS tag sequence for a given sentence
Design part-of-speech taggers from scratch
Recognize the limitations of context free grammars and analyse the extensions to CFG
Apply well-known parsing algorithms to natural language data
Recognize the limitations of parsing algorithms and improve them using differnet methods.
Understand the principles of natural language meaning
Analyse and Compare different representations for semantics
Describe state of the art methods for NLP applications such as text categorization, information extraction etc.
Recognize the computational problems associated to natural language recognition and parsing
Design , implement and evaluate an NLP system
Program Outcomes Matrix
| Contribution | |||||
| # | Program Outcomes | No | Yes | ||
| 1 | An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics | ✔ | |||
| 2 | An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors | ✔ | |||
| 3 | An ability to communicate effectively with a range of audiences | ✔ | |||
| 4 | An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts | ✔ | |||
| 5 | An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives | ✔ | |||
| 6 | An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions | ✔ | |||
| 7 | An ability to acquire and apply new knowledge as needed, using appropriate learning strategies | ✔ | |||