Knowledge Technologies
Subject COMP30018 (2012)
Note: This is an archived Handbook entry from 2012.
Credit Points: | 12.50 | ||||||||||||
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Level: | 3 (Undergraduate) | ||||||||||||
Dates & Locations: | This subject has the following teaching availabilities in 2012: Semester 2, 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: 120 hours | ||||||||||||
Prerequisites: | One of the following: Subject Study Period Commencement: Credit Points: | ||||||||||||
Corequisites: | None | ||||||||||||
Recommended Background Knowledge: | None | ||||||||||||
Non Allowed Subjects: | Subject 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/ |
Coordinator
Assoc Prof Tim BaldwinContact
Associate Professor Tim Baldwin
email: tbaldwin@unimelb.edu.au
Subject Overview: |
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. |
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Objectives: |
On completion of the subject, students should be able to:
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Assessment: |
To pass the subject, students must obtain at least:
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Prescribed Texts: | TBA |
Breadth Options: | This subject potentially can be taken as a breadth subject component for the following courses: You should visit learn more about breadth subjects and read the breadth requirements for your degree, and should discuss your choice with your student adviser, before deciding on your subjects. |
Fees Information: | Subject EFTSL, Level, Discipline & Census Date |
Related Course(s): |
Bachelor of Engineering (Software Engineering) Bachelor of Engineering (Software Engineering)/Bachelor of Science |
Related Majors/Minors/Specialisations: |
B-ENG Software Engineering stream Computer Science Computer Science Computing and Software Systems Master of Engineering (Software) Science credit subjects* for pre-2008 BSc, BASc and combined degree science courses Science-credited subjects - new generation B-SCI and B-ENG. Core selective subjects for B-BMED. Software Systems |
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