A comment yesterday:
However, the first step would be to create a catalog of common topic map structures or patterns. It seems like such a catalog could eventually enable automated or computer assisted construction of topic maps to supplement hand-editing of topic maps. Hand-editing is a necessary first step but it does not scale well. Imagine how few applications there would be now if everything had to be coded in assembler. Or how few databases would there be now if everyone had to build their own out of B-Trees. (Carl)
resonated when I was writing an entry about computational linguistics today.
I think Carl is right, people don’t create their own databases out of B-Trees.
But by the same token, they don’t forge completely new patterns of speaking either.
I don’t know what the numbers are, but how many original constructions in your native language do you use every day? Particularly in a professional setting?
Rather than looking for “topic map” patterns, shouldn’t we be looking for speech patterns in particular user communities?
Such that our interfaces, when set to a particular community, can automatically parse input into a topic map.
Not unconstrained subject recognition but using language patterns to capture some percentage of subjects rather than the user.