Natural Language Understanding (2013/2014)

Course Overview

This course explores current research into interpreting natural language. Motivations for this study range from foundational attempts to understand how people interpret communication to entirely practical efforts to engineer systems for performing a variety of language tasks, such as information extraction, question answering, natural language front ends to databases, human-robot interaction and customer relationship management, to name a few.

This course represents an introduction to the theory and practice of computational approaches to natural language understanding. The course will cover common parsing methods for sentences, discourse and dialogue, and it will also address lexical processing tasks such as word sense disambiguation and clustering. We will study state of the art symbolic techniques in deep and shallow language processing, as well as statistical models, acquired by both unsupervised and supervised machine learning from online linguistic resources. Students will have the opportunity to explore what they have learned in written and practical assignments. These assignments will be designed to enable students to gain an understanding for the pervasiveness of language ambiguity at all levels and the problems this poses for automated language understanding, and for the relative strengths and weaknesses of the various theories and engineering approaches to these problems.

Mailing List

Announcements regarding the course will be posted to the course mailing list. All students taking the course are automatically subscribed to this list. Previous postings can be accessed using the mailing list archive.

Software

We will use NLTK for the assignments of this course. NLTK is installed on all Dice machines; if you don't have a Dice account, please apply for one as soon as possible.


Home : Teaching : Courses 

Informatics Forum, 10 Crichton Street, Edinburgh, EH8 9AB, Scotland, UK
Tel: +44 131 651 5661, Fax: +44 131 651 1426, E-mail: school-office@inf.ed.ac.uk
Please contact our webadmin with any comments or corrections. Logging and Cookies
Unless explicitly stated otherwise, all material is copyright © The University of Edinburgh