This is an AI question more than anything else, so I'll sling it here, unless anyone knows of anyplace else more relevent for it:
The Guardian, www.guardian.co.uk, seems to encourage people to pass around their content, as long as it's credited (See: http://www.guardian.co.uk/Distribution/CDistr_Help/ ). And I enjoy reading The Guardian, so for a few weeks now, I've been basically using their "content distribution" facilities to just mirror each day's new stories to my hard drive, so I can read the paper while I'm offline. (I'm not actually redistributing the content to others.) It's about 120 stories of basically plaintext every day, about 500K a day. So after a while of having these stories download every day, I started thinking that it wouldn't be hard to make up a system where people selected the /kinds/ of news they're interested in; and, then based on that, a program could point them at the most relevent stories in a given day's news. But with finer grain than just "I like stories in the tech Technology section, and nothing from the Sports section!" More like an Amazon recommendation system, but for news stories. I'm sure systems like this must exist, but I've never seen one. Ideas? Examples? -- Sean M. Burke [EMAIL PROTECTED] http://www.spinn.net/~sburke/
