NATURAL LANGUAGE PROCESSING

CSE5NLP

Not currently offered

Credit points: 15

Subject outline

Natural Language Processing (NLP) is broadly concerned with the interactions between computers and natural (i.e., human) languages; more particularly, it is concerned with the question of how to program computers to process and analyse large amounts of natural language data. Following a review of the essential mathematical and linguistic concepts underlying natural language processing, you will develop skills in important natural language processing sub-tasks including accessing corpora, tokenisation, morphological analysis, word sense disambiguation, part-of speech tagging, and analysing sentence structure. You will then apply these skills in the context of applications such as text categorisation, text clustering, text recommendation, and information retrieval. Where appropriate, both lexical (i.e. dictionary-based) and machine learning approaches will be used.

School: Engineering and Mathematical Sciences (Pre 2022)

Credit points: 15

Subject Co-ordinator: Andrew Skabar

Available to Study Abroad/Exchange Students: Yes

Subject year level: Year Level 5 - Masters

Available as Elective: No

Learning Activities: N/A

Capstone subject: No

Subject particulars

Subject rules

Prerequisites: CSE2AIF OR CSE5AIF

Co-requisites: N/A

Incompatible subjects: N/A

Equivalent subjects: N/A

Quota Management Strategy: N/A

Quota-conditions or rules: N/A

Special conditions: N/A

Minimum credit point requirement: N/A

Assumed knowledge: N/A

Learning resources

Speech and Language Processing

Resource Type: Book

Resource Requirement: Recommended

Author: Daniel Jurafsky and James H. Martin.

Year: 2014

Edition/Volume: N/A

Publisher: Pearson

ISBN: N/A

Chapter/article title: N/A

Chapter/issue: N/A

URL: N/A

Other description: N/A

Source location: N/A

Foundations of Statistical Natural Language Processing

Resource Type: Book

Resource Requirement: Recommended

Author: Christopher D. Manning and Hinrich Schutze.

Year: 1999

Edition/Volume: N/A

Publisher: The MIT Press

ISBN: N/A

Chapter/article title: N/A

Chapter/issue: N/A

URL: N/A

Other description: N/A

Source location: N/A

Natural Language Processing with Python

Resource Type: Book

Resource Requirement: Recommended

Author: Steven Bird, Ewan Klein & Edward Loper

Year: N/A

Edition/Volume: N/A

Publisher: O'Reilly

ISBN: N/A

Chapter/article title: N/A

Chapter/issue: N/A

URL: N/A

Other description: N/A

Source location: N/A

Career Ready

Career-focused: No

Work-based learning: No

Self sourced or Uni sourced: N/A

Entire subject or partial subject: N/A

Total hours/days required: N/A

Location of WBL activity (region): N/A

WBL addtional requirements: N/A

Graduate capabilities & intended learning outcomes

Graduate Capabilities

Intended Learning Outcomes

01. Apply natural language processing sub tasks, including tokenisation, morphological analysis, word sense disambiguation, part-of-speech tagging, and analysing sentence structure, to natural languages texts.
02. Describe and evaluate the methods and algorithms used to process different types of textual data.
03. Devise natural language processing (NLP)processing pipelines using existing NLP code libraries, text corpora, and lexical resources such as WordNet.
04. Critically evaluate results of applying natural language processing methods to real-world tasks such as text categorisation, text clustering, text recommendation and information retrieval.
Subject not currently offered - Subject options not available.