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Information Retrieval Research Group

Currently, the following members of academic staff are associated with this group:
Andrew Trotman

The work of the Group

There is more electronic information available than we could possibly process in a lifetime, so we must rely on search engines and collaborative filtering tools to process and sift data in an effort to answer our questions. Since knowledge is power, the value of these tools indisputable.

Our group is working in many areas of information retrieval from the efficiency of the search engine, to effective ranking, evaluation, and human / computer interaction. We have an engineering focus and much of our work is driven by the implementation of our search engine. The Architecture of a modern computer is quite different from that of only 5 years ago, we are seeing multi-core, hyper-threading, SIMD, GPGPU and other architectures on the desktop and in mobile devices. It is not at all clear how to take full advantage of this new technology. Consequently, we are exploring fundamental aspects of what a computer is, and how to manage resources, so that the search engines of the future will be both faster and more efficient (greener) than today. Our work on SIMD has led to new and fast to decode compression schemes. Our work on evaluation has led to new ways of managing uncertainty. Our work on link discovery has led to new ways to automatically recommend hypertext links in documents. We have also worked extensively on Focused Retrieval and with Semi-Structured data.

We are also interested in Collaborative Filtering, Recommendation, and text and data mining. This technology is well established as movie, book, and music recommenders, but is it also seen in traditional search engines with 'more like this' functionality and in product recommendation on eCommerce sites.

If search engine technologies, data mining, or any sort of information discovery (quantitative or qualitative) appeals to you, call by and have a chat with us - we're happy to hear from you.