cse5nlp natural language processing

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.

SchoolEngineering and Mathematical Sciences

Credit points15

Subject Co-ordinatorAndrew Skabar

Available to Study Abroad/Exchange StudentsYes

Subject year levelYear Level 5 - Masters

Available as ElectiveNo

Learning ActivitiesN/A

Capstone subjectNo

Subject particulars

Subject rules

PrerequisitesCSE2AIF OR CSE5AIF

Co-requisitesN/A

Incompatible subjectsN/A

Equivalent subjectsN/A

Quota Management StrategyN/A

Quota-conditions or rulesN/A

Special conditionsN/A

Minimum credit point requirementN/A

Assumed knowledgeN/A

Learning resources

Speech and Language Processing

Resource TypeBook

Resource RequirementRecommended

AuthorDaniel Jurafsky and James H. Martin.

Year2014

Edition/VolumeN/A

PublisherPearson

ISBNN/A

Chapter/article titleN/A

Chapter/issueN/A

URLN/A

Other descriptionN/A

Source locationN/A

Foundations of Statistical Natural Language Processing

Resource TypeBook

Resource RequirementRecommended

AuthorChristopher D. Manning and Hinrich Schutze.

Year1999

Edition/VolumeN/A

PublisherThe MIT Press

ISBNN/A

Chapter/article titleN/A

Chapter/issueN/A

URLN/A

Other descriptionN/A

Source locationN/A

Natural Language Processing with Python

Resource TypeBook

Resource RequirementRecommended

AuthorSteven Bird, Ewan Klein & Edward Loper

YearN/A

Edition/VolumeN/A

PublisherO'Reilly

ISBNN/A

Chapter/article titleN/A

Chapter/issueN/A

URLN/A

Other descriptionN/A

Source locationN/A

Career Ready

Career-focusedNo

Work-based learningNo

Self sourced or Uni sourcedN/A

Entire subject or partial subjectN/A

Total hours/days requiredN/A

Location of WBL activity (region)N/A

WBL addtional requirementsN/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.

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