On Thu, 19 Apr 2001, Sam Joseph wrote:
> > Well, that's kind of what I'm working on with NeuroGrid now. It's not > set up yet, but my approach is to get a person's bookmark file, extract > all of the urls out of it, download each of those pages, chew them up, > spit out all the tags, and then use some basic information retrieval > statistics (like TFIDF - term frequency inverse document frequency) to > work out which subset of keywords are relevant and use those as the > basis for a user's NeuroGrid profile. > > One could go so far as to try and create ranks based on the TFIDF and > then translate them into usage ranks, like the ones I described, but I > think they are just a very different kind of thing, and the idea with NG > is that user's should be able to edit all the associations between > keywords and their bookmarks, it should all be personalised. So I would > imagine using the bookmark file as a way to get some urls into the > system, a little TFIDF to provide base associations and then let the > searching do its work. NG searching allows urls to become associated > with other keywords through multiple keyword searches and so on, so I'm
