Databases and Information Retrieval
If a search led you to this page, you have already experienced information retrieval in action. Behind every successful search lies a sophisticated combination of indexing techniques, data structures, and algorithms that enable relevant information to be located efficiently within vast collections of data.
Information Retrieval (IR) is concerned with the representation, organisation, and access of information at scale. It focuses on developing methods to identify and rank the most relevant results from large and often unstructured data sources, including text, multimedia, and web-scale collections. Complementing this, research in Databases addresses the efficient storage, structuring, and management of data, ensuring that information can be retrieved quickly, reliably, and at scale.
Our research explores the interplay between database technologies and information retrieval methods. We we aim to improve the performance, scalability, and effectiveness of systems that underpin search engines, digital libraries, and other large-scale information platforms.
Staff
Prof Justin Zobel
Graduate Researchers
Kasun Amarasinghe
Learning index structure for multi-dimensional spatial data
kasun.amarasinghe@student.unimelb.edu.au
Reyhaneh Goli
User search modelling in complex querying environments
reyhaneh.goli@student.unimelb.edu.auProjects
“New Approaches to Interactive Sessional Search for Complex Tasks”, ARC Discovery Project DP190101113, by Alistair Moffat, joint with Falk Scholer (RMIT University) and Shane Culpepper (University of Queensland).
We work with businesses to:
- Develop clear and simple solutions to create meaning out of your problems
- Provide advice on how to approach and resolve more complex problems
- Embed solutions into daily operations
Interested in how we could help you?
We'd love to chat about how our research could transform your business. We believe collaborating with industry drives both partners forward.
Real world change, based in cutting edge research.