Data and Web Mining

Course aim

To introduce major data and web mining techniques, advanced applications, and new developments. To develop knowledge and skills to discover useful information from data effectively.

Course content

Introduction to data mining and data mining processes.

• Basic data mining techniques: data preprocessing,  association mining, classification, and clustering.
• Advanced applications: textual data mining,  and Web mining.
• Data mining software tools and using a software tool to solve some simple real world data mining problems.

Textbook(s)

Pang-Ning tan, Michael Steinbach, and Vipin Kumar 2006, Introduction to Data Mining, Pearson Higher Education

Prerequisite(s)

Nil

Corequisite(s)

Nil

Teaching method

Component	Duration
INTERNAL, MAWSON LAKES
Lecture	3 hrs x 13 weeks
Practical	1 hr x 11 weeks

Note: These components may or may not be scheduled in every study period. Please refer to the timetable for further details.

Assessment

Data and data preprocess, Data mining process, Examination

Fees

EFTSL*: 0.125
Commonwealth Supported program (Band 2)
To determine the fee for this course as part of a Commonwealth Supported program, go to:
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Fee-paying program for domestic and international students
International students and students undertaking this course as part of a postgraduate fee paying program must refer to the relevant program home page to determine the cost for undertaking this course.

Non-award enrolment
Non-award tuition fees are set by the university. To determine the cost of this course, go to:
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Not all courses are available on all of the above bases, and students must check to ensure that they are permitted to enrol in a particular course.

* Equivalent Full Time Study Load. Please note: all EFTSL values are published and calculated at ten decimal places. Values are displayed to three decimal places for ease of interpretation.