annej - 1:20 am on May 24, 2007 (gmt 0)

Well I finally finished the two big projects that have been keeping me from reading patents. But today they are done and all that was left was to clean my neglected house or read patents. Well, given that choice what would anyone do" ;)

I am just beginning to get some impressions and I certainly don't completly understand all I read in them. But I want to see if I'm on the right track so here is what they seem to be indicating.

Through an involved process they would sort out phrases between good phrases and bad phrases. Good phrases are those that are predictive of other good phrases while bad phrases are not useful in terms of prediction. For example bad would include very infrequent phrases, common sayings that could be in a document on many topics like "that's the way it goes" as well as for other reasons.

There are many refinements in this but in the end the process would determine if a document included more than one phrase that would predictably be seen together in a given topic. That would be matched with the query phrase. (not word for word but more on a conceptual level).

Certain phrases in a document would be given more weight including phrases that are bolded, in quotes and in anchor text. Both ingoing and outgoing anchor text would be considered.

Somehow with this mix of information documents would be ranked in relationship with the query.

This process would actually take less computer space etc than the traditional way of considering every word on a page. Instead only qualified phrases would be considered.

I have questions and thoughts on all this but for starters I need to know if I'm even on the right track on how this would work. Any thoughts or clarifications anyone?