This course will introduce students to computational linguistics (CL) and natural language processing (NLP), a field combining insights from linguistics and computer science. The course is concerned with concepts, models, and algorithms to interpret, generate, and learn natural languages, as well as applications of NLP.
We will look at these different levels of linguistic analysis: morphology, morpho-syntax, syntax, and lexical semantics. In so doing, we will move from simple representations of language, such as finite-state techniques and n-gram analysis, to more advanced representations, such as those found in context-free and unification-based parsing. Emphasis will be placed on parsing techniques in this course.
|or by appointment|
Academic misconduct is not allowed in this course. The Indiana University Code of Student Rights, Responsibilities, and Conduct (http://dsa.indiana.edu/Code/) defines academic misconduct as ``any activity that tends to undermine the academic integrity of the institution . . . Academic misconduct may involve human, hard-copy, or electronic resources . . . Academic misconduct includes, but is not limited to . . . cheating, fabrication, plagiarism, interference, violation of course rules, and facilitating academic misconduct'' (II. G.1-6).
Students who need an accommodation based on the impact of a disability should contact me to arrange an appointment as soon as possible to discuss the course format, to anticipate needs, and to explore potential accommodations.
I rely on Disability Services for Students for assistance in verifying the need for accommodations and developing accommodation strategies. Students who have not previously contacted Disability Services are encouraged to do so (812-855-7578; http://www.indiana.edu/~iubdss/).
|Jan.||11||Intro to class (.pdf, 2x3.pdf)||ch. 1|
|13||Regular expressions & Automata (.pdf, 2x3.pdf)||ch. 2|
|18||No class, MLK Day|
|20||Regular expressions & Automata|
|25||Morphology (.ppt)||ch. 3|
|27||Finite-State Transducers (FSTs)||HW1 due|
|Feb.||1||Composition (.pdf, 2x3.pdf)||Roark&Sproat, ch. 2|
|3||N-grams (.pdf, 2x3.pdf)||ch. 4||HW2 due|
|8||Part-of-speech (POS) tagging (.ppt)||ch. 5, 6.1-6.4|
|10||Basics of set theory (.pdf, 2x3.pdf)|
|15||Context-Free Grammars (CFGs) (.pdf, 2x3.pdf)||ch. 12||HW3 due|
|17||CFGs & Parsing (.pdf, 2x3.pdf)||ch. 13|
|22||CFGs & Parsing|
|24||More on chart parsing||HW4 due|
|Mar.||1||Unification-based parsing (.pdf, 2x3.pdf)||ch. 15|
|8||Grammar complexity (.pdf, 2x3.pdf)||ch. 16||HW5 due|
|10||Definite clause grammars|
|22||Partial parsing||sec. 13.5|
|29||Probabilistic parsing (.ppt)||ch. 14||HW6 due|
|31||Semantics (.pdf, 2x3.pdf)||ch. 17|
|7||Semantic analysis||ch. 18||HW7 due|
|14||Lexical semantics (.pdf, 2x3.pdf)||ch. 19|
|19||Word Sense Disambiguation||ch. 20|
|21||Word Sense Disambiguation||HW8 due|
|May||3 (M)||Written projects due, 5pm|