Postgraduate Course: Advanced Natural Language Processing (INFR11059)
Course Outline
| School |
School of Informatics |
College |
College of Science and Engineering |
| Course type |
Standard |
Availability |
Available to all students |
| Credit level (Normal year taken) |
SCQF Level 11 (Postgraduate) |
Credits |
20 |
| Home subject area |
Informatics |
Other subject area |
None |
| Course website |
http://www.inf.ed.ac.uk/teaching/courses/ |
|
|
| Course description |
The course will synthesize recent research in linguistics, computer science, and natural language processing with the aim of introducing students to theoretical and computational models of language. The course will familiarize students with a wide range of linguistic phenomena with the aim of appreciating the complexity, but also the systematic behaviour of natural languages like English, the pervasiveness of ambiguity, and how this presents challenges in natural language processing. In addition, the course introduce the most important algorithms and data structures that are commonly used to solve many NLP problems.
The course will cover formal models for representing and analyzing syntax and semantics of words, sentences, and discourse. Students will learn how to analyse sentences algorithmically, using hand-crafted and automatically induced treebank grammars, how to make monotonic syntactic derivations, and build interpretable semantic representations. The course will also cover a number of standard algorithms that are used throughout language processing. Examples include Hidden Markov Models, the EM algorithm, and state space algorithms such as dynamic programming. |
Entry Requirements
| Pre-requisites |
|
Co-requisites |
|
| Prohibited Combinations |
Students MUST NOT also be taking
Foundations of Natural Language Processing (INFR09028)
|
Other requirements |
For Informatics PG and final year MInf students only, or by special permission of the School.
CPSLP or equivalent background..
|
| Additional Costs |
None |
Course Delivery Information
|
| Delivery period: 2010/11 Semester 1, Available to all students (SV1)
|
WebCT enabled: No |
Quota: None |
| Location |
Activity |
Description |
Weeks |
Monday |
Tuesday |
Wednesday |
Thursday |
Friday |
| Central | Lecture | | 1-11 | | 09:00 - 09:50 | | | | | Central | Lecture | | 1-11 | | | | | 09:00 - 09:50 |
| First Class |
Week 1, Tuesday, 09:00 - 09:50, Zone: Central. Room 2.12, Appleton Tower |
|
| Delivery period: 2010/11 Semester 1, Part-year visiting students only (VV1)
|
WebCT enabled: No |
Quota: None |
| Location |
Activity |
Description |
Weeks |
Monday |
Tuesday |
Wednesday |
Thursday |
Friday |
| Central | Lecture | | 1-11 | | 09:00 - 09:50 | | | | | Central | Lecture | | 1-11 | | | | | 09:00 - 09:50 |
| First Class |
Week 1, Tuesday, 09:00 - 09:50, Zone: Central. Room 2.12, Appleton Tower |
Summary of Intended Learning Outcomes
1 - Students should be able to construct examples of ambiguous Natural Language sentences and provide a written explanation of how ambiguity arises in natural language and why this is a problem for computational analysis.
2 - Given a grammar, semantics and sentence, students should be able to construct a syntatic and semantic analysis of the sentence.
3 - Given an appropriate NLP problem, students should be able to apply sequence models, parsing and search algorithms and provide a summary of their operation in this context.
4 - Given an appropriate NLP problem, students should be able to analyse the problem and decide which data structures and algorithms to apply. ? Review and classify search algorithms and ways of manipulating dynamic data structures.
5 - Given two NLP algorithms, students should be able to describe how they are related and illustrate differences and limitations by providing illustrative examples. |
Assessment Information
Written Examination 70
Assessed Assignments 30
Oral Presentations 0
There will be three coursework exercises; one on sequence models, one on parsing, and one on applying the methods introduced in the course to an unseen problem.
If delivered in semester 1, this course will have an option for semester 1 only visiting undergraduate students, providing assessment prior to the end of the calendar year. |
| Please see Visiting Student Prospectus website for Visiting Student Assessment information |
Special Arrangements
| Not entered |
Contacts
| Course organiser |
Dr Michael Rovatsos
Tel: (0131 6)51 3263
Email: mrovatso@inf.ed.ac.uk |
Course secretary |
Miss Kate Weston
Tel: (0131 6)50 2701
Email: Kate.Weston@ed.ac.uk |
|
copyright 2010 The University of Edinburgh -
1 September 2010 6:11 am
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