COM6115 Text Processing
| Summary |
This module introduces fundamental concepts and ideas in
natural language text processing, covers techniques for
handling text corpora, and examines representative systems
that require the automated processing of large volumes of
text. The course focuses on modern quantitative techniques
for text analysis and explores important models for
representing and acquiring information from texts. Students should be aware that there are limited places available on this course |
| Session |
Autumn 2023/24 |
| Credits |
15 |
| Assessment |
- Assignment [LOs 1 & 3]
- Formal examination [LOs 2 & 3]
|
| Lecturer(s) |
Prof. Aline Villavicencio & Dr Chenghua Lin |
| Resources |
|
| Aims |
- to develop an understanding of the fundamentals of
text processing;
- to acquire familiarity with techniques for handling
text corpora;
- to develop an understanding of the basic problems and
principles underlying text processing applications.
|
| Learning Outcomes |
By the end of this unit, a candidate should be able to:
- code in a programming language well-suited to text
handling
- identify and explain key techniques that are relevant
to performing a number of text processing tasks
- implement systems able to analyse large volumes of
textual data, and to perform basic, and in selected cases, more advanced text processing tasks
|
| Content |
- Programming for text processing
- Linguistic background
- Text processing topics, such as:
- Information retrieval
- Natural language generation
- Information Extraction
- Sentiment analysis
|
| Teaching Method |
- There will be 2 lectures per week, with not more than 20
lectures overall.
- A third session will be available for lab classes or
tutorials some weeks.
|
| Feedback |
Students can discuss their lab exercise code during lab
sessions. They will receive feedback comments on their
marked assignment work later on in the term (prior to the
exam). |
|
