Course Title: Information Retrieval

Part A: Course Overview

Course Title: Information Retrieval

Credit Points: 12

Course Coordinator: Dr. Falk Scholer

Course Coordinator Phone: +61 3 9925 9831

Course Coordinator Email:falk.scholer@rmit.edu.au

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.

You should be able to program in Java or C, and have knowledge of core data structures and algorithms, equivalent to Programming 2 Programming Techniques. You should also have an understanding of maths (the equivalent of year 12), especially (vector) inner products and probability.

Course Description

The Internet is the world’s largest collection of information. Search engines are the key enabling technology to help users to find useful material among the billions of available resources.

In this course you will learn about the techniques used to retrieve useful information from repositories such as the Web. The course first introduces standard concepts in information retrieval such as documents, queries, collections, and relevance. Efficient indexing, to allow for the quick identification of candidate answer documents, is considered. To find the best answers, a range of querying approaches (such as Boolean and Ranked retrieval) are studied.  The course then covers a selection of application areas such as music search, document summarisation, cross-lingual retrieval, and image retrieval.

Objectives/Learning Outcomes/Capability Development

On completion of this course you should have gained a good understanding of the foundation concepts of information retrieval techniques and be able to apply these concepts into practice. Specifically, you should be able to:

• use different information retrieval techniques in various application areas
• apply IR principles to locate relevant information large collections of data
• analyse performance of retrieval systems when dealing with unmanaged data sources
• implement retrieval systems for web search tasks.

Overview of Learning Activities

Syllabus material will be presented, explained and illustrated with demonstrations and examples in lectures, classes, or online. The lecture material comes in part from the lecture notes, from research papers and from the lecturer’s own experience. It is designed so that you are able to follow examples during lectures, undertake additional exercises and discussions in tutorials and follow up with further examples in the notes. You are encouraged to participate in all sessions through questions and discussion.
Laboratory experiences include exercises using and building information retrieval systems.
Critical thinking and analysis will be developed through review of current research literature in the area.
Completion of tutorial questions and laboratory programming exercises and projects, are designed to give further practice in the application of theory and procedures, and to give feedback on your progress and understanding. Private study will consolidate your understanding of the theory and practice.

Overview of Learning Resources

You will make extensive use of computer laboratories and relevant software provided by the School. You will be able to access course information and learning materials through the Learning Hub (also known as online@RMIT) and may 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.

Use the RMIT Bookshop’s textbook list search page to find any recommended textbook(s).

Overview of Assessment

The assessment for this course comprises practical work and a final exam.

For standard assessment details, including deadlines, weightings, and hurdle requirements relating to Computer Science and IT courses see: http://www.rmit.edu.au/compsci/cgi