Note: This is an archived Handbook entry from 2012.
|Dates & Locations:|| |
This subject has the following teaching availabilities in 2012:Semester 1, Parkville - Taught on campus.
Timetable can be viewed here. For information about these dates, click here.
|Time Commitment:||Contact Hours: 24 one-hour lectures (two per week) and 12 one-hour workshops (one per week) |
Total Time Commitment:
One of the following:
Study Period Commencement:
Semester 1, Semester 2
Semester 1, Semester 2
433-253 Algorithms and Data Structures
|Recommended Background Knowledge:|| |
|Non Allowed Subjects:|| |
433-352 Data on the Web
|Core Participation Requirements:||
For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Students Experiencing Academic Disadvantage Policy, academic requirements for this subject are articulated in the Subject Description, Subject Objectives, Generic Skills and Assessment Requirements of this entry.The University is dedicated to provide support to those with special requirements. Further details on the Disability support scheme can be found at the Disability Liaison Unit Website:http://www.services.unimelb.edu.au/disability/
CoordinatorProf Justin Zobel, Prof Rao Kotagiri
Dr Aaron Harwood
Much of the world's knowledge is stored in the form of unstructured data (e.g. text) or implicitly in structured data (e.g. databases). In this subject students will learn algorithms and data structures for extracting, retrieving and storing explicit knowledge from various data sources, with a focus on the web. Topics include: data encoding and markup, web crawling, clustering, regular expressions, pattern mining, Bayesian learning, instance-based learning, document indexing, database storage and indexing, and text retrieval.
On successful completion of the subject, students should be able to:
To pass the subject, students must obtain at least:
|Prescribed Texts:|| |
|Breadth Options:|| |
This subject is not available as a breadth subject.
|Fees Information:||Subject EFTSL, Level, Discipline & Census Date|
On completion of this subject students should have developed the following generic skills:
Master of Engineering in Distributed Computing |
Master of Information Technology
Master of Science (Computer Science)
Master of Software Systems Engineering
Computer Science |
Master of Engineering (Software)
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