• Offered by Research School of Computer Science
  • ANU College ANU College of Engineering and Computer Science
  • Classification Advanced
  • Course subject Computer Science
  • Academic career Postgraduate
  • Course convener
    • Dr Scott Sanner
  • Mode of delivery In Person
  • Co-taught Course COMP4650
  • Offered in Second Semester 2016
    See Future Offerings

Processing of semi-structured documents such as internet pages, RSS feeds and their accompanying news items, and PDF brochures is considered from the perspective of interpreting the content. This course considers the \document" and its various genres as a fundamental object for business, government and community. For this, the course covers four broad areas: (A) information retrieval, (B) natural language processing, (C) machine learning for documents, and (D) relevant tools for the Web. Basic tasks here are covered including content collection and extraction, formal and informal natural language processing, information extraction, information retrieval, classification and analysis. Fundamental probabilistic techniques for performing these tasks, and some common software systems will be covered, though no area will be covered in any depth.

Learning Outcomes

Upon successful completion of the course, the student will have an understanding of the role documents play in business and community, and the various digital resources available for document analysis. Moreover, the student will have the background theory and practical knowledge necessary to plan and execute a basic document analysis project. The student will be able to:
  • differentiate between the basic probabilistic theories of language and document structure, information retrieval, and classification, clustering and document feature engineering.
  • identify the basic algorithms and software available for probabilistic theories of language and be proficient at using common libraries for natural language processing to perform basic analysis tasks.
  • index a document collection for use in an information retrieval system. Demonstrate advanced knowledge of basic theories and algorithms to determine large scale named-entity matching and standardization of names within a collection.
  • perform automated classification using probabilistic theories.

Indicative Assessment

Assignments (40%); Written final exam (60%)

The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.

Workload

Thirty one-hour lectures and six two hour tutorial/laboratory sessions

Requisite and Incompatibility

You are not able to enrol in this course if you have successfully completed COMP4650.

Prescribed Texts

The following reference books will be used.

  • Introduction to Information Retrieval, C.D. Manning, P. Raghavan and H. Scutze, Cambridge University Press, 2008.
  • Foundations of Statistical Natural Language Processing, C.D. Manning and H. Scutze, MIT Press, 1999.

Assumed Knowledge

Programming ability in C, C++ or Java, and basic mathematical and statistical knowledge, at an undergraduate-level

Specialisations

Fees

Tuition fees are for the academic year indicated at the top of the page.  

If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.

Student Contribution Band:
Band 2
Unit value:
6 units

If you are an undergraduate student and have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). You can find your student contribution amount for each course at Fees.  Where there is a unit range displayed for this course, not all unit options below may be available.

Units EFTSL
6.00 0.12500
Domestic fee paying students
Year Fee
2016 $3480
International fee paying students
Year Fee
2016 $4638
Note: Please note that fee information is for current year only.

Offerings and Dates

The list of offerings for future years is indicative only

Second Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery
8351 18 Jul 2016 29 Jul 2016 31 Aug 2016 28 Oct 2016 In Person

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