| EPSRC Reference: |
GR/T18455/01 |
| Title: |
Super-Computing Data Mining |
| Principal Investigator: |
Bull, Professor L |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
Faculty of Environment and Technology |
| Organisation: |
University of the West of England |
| Scheme: |
Standard Research (Pre-FEC) |
| Starts: |
01 January 2005 |
Ends: |
31 March 2007 |
Value (£): |
102,784
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| EPSRC Research Topic Classifications: |
| Information & Knowledge Mgmt |
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| EPSRC Industrial Sector Classifications: |
| No relevance to Underpinning Sectors |
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Summary on Grant Application Form |
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There is now widespread recognition that it is possible to extract previously unknown knowledge from large datasets using machine learning techniques. As the use of machine learning for exploratory data analysis has increased, so have the sizes of the datasets they must face (Giga and Terabyte datasets are common place) and the sophistication of the algorithms themselves. For this reason there is a growing body of research concerned with the use of parallel computing for data mining. The aim of this project is to produce a super-computing data mining resource for use by the UK academic community which utilises a number of advanced machine learning and statistical algorithms for large datasets. In particular, a number of evolutionary computing-based algorithms and the ensemble machine approach will be used to exploit the large-scale parallelism possible in super-computing.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.uwe.ac.uk |