|Drat. I fell asleep just after I emailed. Helena - you hit the master question there. Here's how we think it goes at the moment. |
You can find similarities between hunches in many different ways, e.g.
Linking evidence to hunches gives you something close to a naive Bayes (or other uncertainly-handling equlivalent) system - no more than one link at a time, no (or very few) messy interactions between links. But as soon as you start linking hunches, what you've got on your hands is a full-blown reasoning system, with concepts like generalisation/specialisation, reasoning chains, uncertainty handling and argumentation. And that gets you quickly into places like inductive logic programming.
Which is a long way of saying that in order to build something that *looks* like a very simple system (think Google search), we have to do some serious research into artificial reasoning methods. What we probably need most right now is some good examples - does anyone want to post some ideas for this? I'm still at the "I think there's a drought in Sudan"... "food prices are rising in Kenya" stage, and I'm sure you all have much better examples than that.
--- On Fri, 13/5/11, Helena Puig Larrauri <hpuigl...@gmail.com> wrote:
I'm wondering if there might be clues in qualitative data analysis software like Atlas.ti or TAMS Analyzer? These tools take text and create various analyses including mapping of how close the concepts are to each other - and logical links between them as well as some quantitate analysis. It wouldn't get into the depth of each hunch, but something like that might be useful in automating a collaborative search for truth.
I would think that hunches mutate and refine over time, and I wonder if there is any way the humans could interact real-time (via webchat or skype, for example) as hunches mature so at some point you go beyond aggregating or accumulating data toward creating a whole picture of a certain situation/hunch.
I''m looking at this from a systems thinking perspective...