I had been searching about the topic but can’t find anything specific about it, the ones that always pop up are k-nn, genetic algorithms, bayesians networks, clustering and decision trees. So after a while I was wondering if is really viable the use of agents, Q learning for content suggestion? Thanks in advanced.
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not exactly _content_ suggestion but quite close, see "dueling bandits" by Y. Yue and T. Joachims
http://www.yisongyue.com/publications/jcss2012_dueling_bandit.pdf
the point is that content recommendation is almost always contextual : users'profile information is often more important than the overall success rate of an item (otherwise, keep recommending blockbusters and you're fine !)
this brings you to "contextual bandits", "bandits with side information" and so on ...
by the way, googling _Reinforced Learning for content recommendation_ will lead you to quite a crowd of interesting publications !
https://www.google.fr/search?q=Reinforced+Learning+for+content+recommendation&ie=utf-8&oe=utf-8&rls=org.mozilla:fr:official&client=firefox-a&gfe_rd=ctrl&ei=ux4eU7nKMInf8gf-0YHwCg&gws_rd=cr#q=Reinforced+Learning+for+content+recommendation&rls=org.mozilla:fr:official&safe=off
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Thanks a lot!!!!, I found lots of interesting articles, I guess I was doing the search with a wrong criteria .... very embarrassed. Again thanks for the quick response.
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