From Natural Language to Bayesian Networks (and back again)
42 mins 7 secs,
77.05 MB,
MP3
44100 Hz,
249.77 kbits/sec
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About this item
| Description: |
Bex, F
Wednesday 28th September 2016 - 10:15 to 11:00 |
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| Created: | 2016-10-05 12:18 |
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| Collection: | Probability and Statistics in Forensic Science |
| Publisher: | Isaac Newton Institute |
| Copyright: | Bex, F |
| Language: | eng (English) |
| Distribution: |
World
(downloadable)
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| Explicit content: | No |
| Aspect Ratio: | 16:9 |
| Screencast: | No |
| Bumper: | UCS Default |
| Trailer: | UCS Default |
| Abstract: | Decision makers and analysts often use informal, linguistic concepts when they talk about a case: they tell the story that explains the evidence, or argue against a particular interpretation of the evidence. On the other hand, mathematicians and logicians present formal frameworks to precisely capture and support reasoning about evidence.
In this talk, I will show how different Artificial Intelligence techniques can be used to close the gap between these two extremes - messy, informal natural language and specific, well-defined formalisms such as Bayesian Networks. |
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