Understanding how people search for information.
Finding the right information is the key to success in the digital age. The IIR group specialises in understanding how people search for information and developing interactive search tools that support their information seeking and retrieval work tasks. The IIR group takes a holistic approach to studying users and their search behaviours, developing tools and interfaces that provide effective and efficient access to heterogeneous, unstructured multi-media collections of information. Our group combines research from Human-Computer Interaction (HCI) and Information Retrieval (IR) bringing together theory and practice.
Our research focuses on users in a variety of domains, where we develop and evaluate novel interfaces and systems, which is underpinned by theory and formal models.
Domains and sectors
Understanding information seeking behaviour and tasks in a variety of settings including healthcare, Patent, News and Media, Academia, Fraud, Security and Culture Heritage; as well as different kinds of users: adults, children (from toddlers to teens), students, elderly, experts, people with impairments and disabilities.
Interfaces and systems
Designing interactive user interfaces and visualisation techniques for studying users' behaviour in various settings: web, Digital Libraries, Collaborative, Mobile, Tablet, Voice & Gesture. Developing intelligent search agents to help support task completion and new systems for personal information management.
Evaluating interactive information retrieval systems and interfaces by developing methods and measures of success.
Modelling the interaction between users and search systems using Economic Theory, Decision Theory, Optimal Foraging Theory, Transportation Planning Theory, etc. to describe, predict and explain search and search behaviours.
Developing retrieval and information filtering algorithms and models including topic modelling, distributed information retrieval, summarization, information extraction, structured data retrieval and text mining to tackle information retrieval problems.
Relevance, benefit and usefulness
Understanding implicit, explicit and effective feedback to model relevance, measuring and model the benefit and usefulness associated with information interactions.
Work with us
Please contact us to talk about potential new projects, collaborations, membership, or joining us as a graduate student or visiting researcher.