Web Search and Text Analysis

Subject COMP90042 (2013)

Note: This is an archived Handbook entry from 2013.

Credit Points: 12.50
Level: 9 (Graduate/Postgraduate)
Dates & Locations:

This subject is not offered in 2013.

Time Commitment: Contact Hours: 36 hours, comprising of one 2-hour lecture and one 1-hour workshop per week
Total Time Commitment:

120 hours


One of the following:

Study Period Commencement:
Credit Points:
Not offered in 2013
Not offered in 2013


Recommended Background Knowledge:


Non Allowed Subjects:

433-460 Human Language Technology
433-467 Text and Document Management
433-660 Human Language Technology
433-667 Text and Document Management
433-476 Text and Document Management

Core Participation Requirements:

For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Student Support and Engagement Policy, academic requirements for this subject are articulated in the Subject Overview, Learning Outcomes, Assessment and Generic Skills sections of this entry.

It is University policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact on meeting the requirements of this subject are encouraged to discuss this matter with a Faculty Student Adviser and Student Equity and Disability Support: http://services.unimelb.edu.au/disability


Associate Professor Tim Baldwin

email: tbaldwin@unimelb.edu.au

Subject Overview:

The aims for this subject is for students to develop an understanding of the main algorithms used in natural language processing and text retrieval, for use in a diverse range of applications including search engines, cross-language information retrieval, machine translation, text mining, question answering, summarisation, and grammar correction. Topics to be covered include text normalisation, sentence boundary detection, part-of-speech tagging, n-gram language modelling, and text classification. The programming language used is Python.


On completion of this subject students should be able to:

  • Articulate issues relevant to the efficient implementation of language processing systems and text retrieval systems
  • Apply natural language processing and information retrieval methodologies to textual data
  • Develop and evaluate computational models of language, based on results from the research literature
  • Apply core information engineering technologies in the management and exploitation of online information

  • Project assignments will be done during the semester and are expected to take approximately 60 hours in total (40%). There are two projects, due around week 6 and week 12. A research-oriented workshop presentation (10%). One 2-hour end-of-semester examination (50%).

  • To pass the subject, students must obtain at least:

50% overall.
25/50 in the continuous assessment.
25/50 in the end-of-semester written examination.

ILO 1, 2 are addressed in the lectures, workshops, and exam; ILO 3, 4 are addressed in the project work and oral presentation.

Prescribed Texts: None
Breadth Options:

This subject is not available as a breadth subject.

Fees Information: Subject EFTSL, Level, Discipline & Census Date
Generic Skills:

On completion of this subject students should have the:

  • Formulate and implement algorithmic solutions to computational problems, with reference to the research literature
  • Apply a systems approach to complex problems, and design for operational efficiency
  • Design, implement and test programs for small and medium size problems in the Python programming language.

Related Course(s): Master of Engineering in Distributed Computing
Master of Information Technology
Master of Information Technology
Master of Information Technology
Master of Philosophy - Engineering
Master of Science (Computer Science)
Master of Software Systems Engineering
Ph.D.- Engineering
Related Majors/Minors/Specialisations: B-ENG Software Engineering stream
Computer Science
Master of Engineering (Software)

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