EPSRC Reference: |
GR/L62849/01 |
Title: |
DEEP DATABASE MINING |
Principal Investigator: |
King, Professor R |
Other Investigators: |
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Researcher Co-Investigators: |
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Project Partners: |
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Department: |
Computer Science |
Organisation: |
Aberystwyth University |
Scheme: |
Standard Research (Pre-FEC) |
Starts: |
01 October 1997 |
Ends: |
30 September 2000 |
Value (£): |
53,295
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EPSRC Research Topic Classifications: |
Information & Knowledge Mgmt |
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EPSRC Industrial Sector Classifications: |
Pharmaceuticals and Biotechnology |
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Related Grants: |
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Panel History: |
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Summary on Grant Application Form |
A central problem in database mining is how to exploit background knowledge. Current databases are poor at using existing knowledge to aid the search for new interesting relationships. What is required is a general data mining search engine that can exploit domain specific modules of background knowledge. To test the feasibility of such a system a demonstration data mining program will be constructed. The general induction engine used by the system will be Inductive Logic Programming, as this form of learning has the greatest ability to use background knowledge. To work with this engine a module of domain specific knowledge will also be created. The problem domain chosen is bioinformatics (the application of computer science to molecular biology). It is a suitable test case because deep background knowledge already exists, and the large datasets being generated require automatic discovery methods for interpretation. A successfully working system will both demonstrate the utility of using background knowledge in data mining, and be a useful tool to biologists.
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Key Findings |
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Potential use in non-academic contexts |
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Impacts |
Description |
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Summary |
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Date Materialised |
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Sectors submitted by the Researcher |
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Project URL: |
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Further Information: |
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Organisation Website: |
http://www.aber.ac.uk |