[Kde-pim] [akregator] Bayesian approach to ease news reading...

[jack]

 Hi!
 I use akregator to read and save all my rss feeds. If you have three
 or five sources it is quite easy to read every day all the new
 messages, but when you have more than 20 it is quite chaotic.. in this
 information overflow era..

 So, using the same maths to classify email messages by spam or ham,
 we can take advantage to know beforehand the probability that a new
 has to be of our interest... well maybe sound a litle bit weird, but
 it is true!!

 Using bogofilter [1] it would be "easy". When you read some new this
 data is considered as ham, and the db is updated. All the news don't
 read are considered as "spam".. then every time you read or not a new
 you are teaching the algorithm. Bogofilter reads a message from stdin
 and returns 0 (spam) or 1 (non-spam).. using that logic it could
 changes the background color of the new.
 That would be the initial idea.

 Is anybody interested in use/development...? Suggestions? Criticism?


[1] http://bogofilter.sourceforge.net/


-- 
Jacobo Avariento Gimeno (jack) || http://ciberjacobo.com
OpenPGP key: http://ciberjacobo.com/key.pem
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