Course Title: Advanced Topics in Search Technology

Part A: Course Overview

Course Title: Advanced Topics in Search Technology

Credit Points: 12.00


Course Code




Learning Mode

Teaching Period(s)


City Campus


140H Computer Science & Information Technology


Sem 1 2006,
Sem 1 2008,
Sem 2 2009,
Sem 2 2010,
Sem 2 2011


City Campus


140H Computer Science & Information Technology


Sem 1 2006,
Sem 1 2008,
Sem 2 2009,
Sem 2 2010,
Sem 2 2011

Course Coordinator: Prof Mark Sanderson

Course Coordinator Phone: +61 3 9925 9675

Course Coordinator Email:

Pre-requisite Courses and Assumed Knowledge and Capabilities

You may not enrol in this course unless it is explicitly listed in your enrolment program summary, and you have confirmed with your program coordinator that it is an appropriate choice for your study plan.

To successfully complete this course, you should have the ability to solve fundamental problems in computing including developing programs, and analyzing algorithms and data structures.

Disclaimer: This seminar-mode course will run only if there are sufficient enrolments by the beginning of the relevant semester. If it is cancelled, you will be advised to choose a suitable alternative course.

Course Description

Search Technology involves the efficient implementation of effective techniques for information retrieval. As this is a seminar course the exact topics will vary from semester to semester depending on the interests of the students and the expertise of the staff involved; thus the following is only illustrative of topics that may be covered.

Text search is a fundamental problem in computer science. Applications of sequence and set-based search include web search engines, genomics, computational biology, network intrusion detection, deep-packet inspection, and many others. Search is now considered a mature research area and a great variety of practical and theoretical algorithms are known. However, efficient search in massive datasets remains an interesting problem with tangible applications.

In this course we will investigate various state-of-the-art algorithms and data structures which support efficient search in massive data collections. In particular, we will focus on algorithms which exploit the memory hierarchy, provide approximate results, or use data compression to reduce the amount of information processed. Our exposition will include the theoretical analysis as well as practical implementation aspects of the algorithms.

Objectives/Learning Outcomes/Capability Development

You will gain capabilities in:
• in-depth technical competence in implementation of search technology,
• ability to creatively design, analyse and synthesise systems and software,
• expectation of the need to undertake lifelong learning, and the capacity to do so.

On successful completion of this course, you will be able to:

  1. Implement selected algorithms for efficient implementation of effective search algorithms,
  2. Compare algorithms using empirical techniques,
  3. Demonstrate selected algorithms on paper,
  4. Recommend solutions to problems based on the properties of the algorithms and techniques studied.

Overview of Learning Activities

This course will be run in a seminar mode where articles are discussed and analysed. In addition to developing knowledge of the content area students will develop skills in critical reading of research literature and in synthesising and comparing approaches to problems.

Students will be expected to participate actively in the discussions, and to take it in turn to lead the discussions. Discussion leadership will involve preparation of focus questions as well as leading of the discussion in class.

Overview of Learning Resources

You will be able to access course information and learning materials through the Learning Hub (also known as online@RMIT) and will be provided with copies of additional materials in class or via email. Lists of relevant reference texts, resources in the library and freely accessible Internet sites will be provided.

Overview of Assessment

The assessment for this course consists of written summaries of reading material, an evaluation of participation in and leading class discussions, a short review paper and a major assignment.

For standard assessment details, including hurdle requirements, relating to Computer Science and IT courses see: