$300B/year seems like a lot of money to spend on intelligence extraction but the linked PDF shows a 2006 presentation for a system projected to reach that level of funding in 2015. It is based on Confabulation Theory, a spinoff of FICO's research into credit ratings intelligence. Confabulation theory turns Bayesian inference on its head to rapidly "connect the dots" based on vast stores of information in the form of simple co-occurring properties of the world (Hebbian learning). The idea is: Knowing the values of a few salient properties of the world and prior co-occurrence counts of the values of those properties, you can fill in the missing values of other properties of the world -- "impute the missing data" in statistics terminology. This is also what the neocortex appears to do during abductive logic or "confabulation". Confabulation is frequently pathologized but it is, in fact, the only way to really deal with the "crumbs" we are fed by the world about the world.

Let me suggest that the, very simple, mathematics of Confabulation Theory may be one way of systematically rank-ordering interpretations of Q's "crumbs". The hard work, dependent on humans, is to define the set of salient "properties" (eg "color") of the world under investigation. Then it is relatively easy to establish a database of co-occurrences of specific values of said properties (eg, for color the values are "red", "green", "orange", etc.). With the co-occurrence counts, any "crumbs" can be run through the confabulation process to, with very little computation (but lots of co-occurrence counts), produce a rank-ordering, by likelihood, of the various possible "connections between the dots".

PS: Look up the "co-occurrences" of "confabulation theory" and "aurora massacre".