Introduction to Computational Linguistics (U01974)

? Credit Points : 10 ? SCQF Level : 9 ? Acronym : INF-3-ICL

Computational Linguistics brings together important aspects of formal linguistics and computation, and this course aims to cover the key concepts and techniques required for research and more specialised study in this rapidly evolving field. In line with contemporary developments, the course is slanted towards shallow processing methods. The following topics will be covered: -An introduction to linguistic models and computational algorithms commonly used in computational linguistics. -The use of standard tools for carrying out representative natural language processing tasks. -The role of computational linguistics in real-world applications.

Entry Requirements

? Pre-requisites : Successful completion of Year 2 of an Informatics Single or Combined Degree, or equivalent by permission of the School. This course assumes no prior experience with linguistics, but students are expected to have some knowledge of an imperative programming language.

Variants

? This course has variants for part year visiting students, as follows

Introduction to Computational Linguistics (VS1) (Semester 1 (Blocks 1-2))

Subject Areas

Home subject area

Language Processing, (School of Informatics, Schedule O)

Delivery Information

? Normal year taken : 3rd year

? Delivery Period : Semester 1 (Blocks 1-2)

? Contact Teaching Time : 3 hour(s) per week for 10 weeks

First Class Information

Date	Start	End	Room	Area	Additional Information
21/09/2006	14:00	14:50	Room G.09, William Robertson Building	Central

All of the following classes

Type	Day	Start	End	Area
Lecture	Monday	14:00	14:50	Central
Lecture	Thursday	14:00	14:50	Central

Summary of Intended Learning Outcomes

After successfully completing the course, students will be able to:
-Describe standard formal models of lexical, morphological and syntactic structure.
-Describe and appraise the main computational algorithms used in part-of-speech tagging and in context free parsing.
-Appraise the utility and feasibility of rule-based and statistical techniques for carrying out representative language processing tasks.
-Use a scripting language to combine various text processing tools into a system.
-Demonstrate an understanding of Gold Standard evaluation methodology.