NATURAL LANGUAGE PROCESSING
Credit points: 15
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
Subject Co-ordinatorFei Liu
Available to Study Abroad/Exchange StudentsYes
Subject year levelYear Level 5 - Masters
Available as ElectiveNo
PrerequisitesCSE5AIF OR CSE2AIF
Quota Management StrategyN/A
Quota-conditions or rulesN/A
Minimum credit point requirementN/A
Speech and Language Processing
AuthorDaniel Jurafsky and James H. Martin.
Foundations of Statistical Natural Language Processing
AuthorChristopher D. Manning and Hinrich Schutze.
PublisherThe MIT Press
Natural Language Processing with Python
AuthorSteven Bird, Ewan Klein & Edward Loper
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
Intended Learning Outcomes
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Melbourne (Bundoora), 2021, Semester 1, Day
Maximum enrolment sizeN/A
Subject Instance Co-ordinatorFei Liu
Computer LaboratoryWeek: 10 - 22
One 2.00 hours computer laboratory per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
LectureWeek: 10 - 22
One 2.00 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
Assignment 1 (equivalent to 1500 words)
Assignment 2 (equivalent to 2,000 words)
|Assignment||Individual||No||30||SILO2, SILO3, SILO4|
Two-hour examination (equivalent to 2,000 words)
|Central exam||Individual||No||50||SILO1, SILO2, SILO3, SILO4|