Traumwind - why bayesian filtering won't cut it in aggregators

I think the bayesian filter approach (as in email/spam) has one major drawback/shortcoming when used for aggregators:
I'm not only interested in one kind of post/topic, but rather a few categories, that can be varied and very different. And also I might on accident find something totally new, which I'd in the future also like to read... A bayesian filter can't help here.

What is needed is a way of 'more like this'... A way to mark posts I like and have the aggregator show me otheres that are similar...

And a list of categories with a 'sample corpus' for each will not really help... categories are to unflexible and not ad-hoc enough to be really easy to use (need thinking about). Similar entries like I have here are a no-brainer user-wise. Just find a post you like and browse fron there...

read this post form some very cool ideas... (using the most intersting tokens to query feedster for other feeds)

[ by Martin>] [permalink] [similar entries]

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similar entries (cg):

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relevant words

Martin Spernau
© 1994-2003

Big things to come (TM) 30th Dez 2002

Accretion
Oblique Strategies, Ed.3 Brian Eno and Peter Schmidt

amazon.de Wunschliste

usefull links:
Google Graph browser
Traumwind 6-Colormatch
UAV News

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