| EPSRC Reference: |
GR/N09152/01 |
| Title: |
INDUCTION OF STOCHASTIC LOGIC PROGRAMS |
| Principal Investigator: |
Cussens, Dr J |
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| Department: |
Computer Science |
| Organisation: |
University of York |
| Scheme: |
Standard Research (Pre-FEC) |
| Starts: |
01 November 2000 |
Ends: |
31 October 2001 |
Value (£): |
49,967
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| No relevance to Underpinning Sectors |
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Summary on Grant Application Form |
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The project aims to develop and implement an algorithm for learning stochastic logic programs (SLPs). SLPs are annotated logic programs with a probailistic operational semantics and are an instance of a class of complex probabilistic models based on log-linear distributions which have been developed in computational linguistics to overcome the limitations of language models such as stochastic context-free grammars.Research into related probabilistic models also exists in the uncertainty in AI community with the aim of overcoming the limitations of graphical probabilistic models such as Bayesian networks.The proposed project aims to combine techniques and algorithms from AI and computational linguistics and to extend them using techniques from Inductive Logic Programming (ILP). ILP is a branch machine learning where logic programs are induced from data and background knowledge. Probabilistic techniques in ILP are, at present, poorly developed so the current project, if successful, will extend the applicability of ILP.
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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 |
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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.york.ac.uk |