Credit points: 15

Subject outline

Data Mining refers to various techniques which can be used to uncover hidden information from a database. The data to be mined may be complex data including multimedia, spatial and temporal data and biological data such as DNA sequences. Data Mining has evolved from several areas including: databases, artificial intelligence, algorithms, information retrieval and statistics. This unit is designed to provide graduate students with a solid understanding of data mining concepts and tools. The unit covers classification rule extraction, clustering algorithms and association rule mining techniques. Domain applications of data mining techniques will be addressed in this unit.

FacultyFaculty of Science, Tech & Engineering

Credit points15

Subject Co-ordinatorPhoebe Chen

Available to Study Abroad StudentsYes

Subject year levelYear Level 4 - UG/Hons/1st Yr PG

Exchange StudentsYes

Subject particulars

Subject rules



Incompatible subjectsN/A

Equivalent subjectsN/A

Special conditionsN/A

Learning resources


Resource TypeTitleResource RequirementAuthor and YearPublisher
ReadingsIntroduction to Data MiningRecommendedTan, PN, Steinback, M & Kumar, V1ST EDN, MORGAN KAUFMANN

Subject options

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Start date between: and    Key dates

Melbourne, 2014, Semester 2, Day


Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorPhoebe Chen

Class requirements

Lecture Week: 31 - 43
One 2.0 hours lecture per week on weekdays during the day from week 31 to week 43 and delivered via face-to-face.

Computer Laboratory Week: 31 - 43
One 2.0 hours computer laboratory per week on weekdays during the day from week 31 to week 43 and delivered via face-to-face.


Assessment elementComments%
Assignemnt 1 equivalent to 1,200 wordsHurdle requirement: In order to pass the unit, students must obtain an overall pass grade, pass the examination and pass the overall non-examination components.20
Assignemnt 2 equivalent to 1,200 words20
one 3-hour examination50
pratical/tutorial participation and contribution to tutorial taks10