Hi
I am looking for a recommender example for news articles which is making
suggestions based on a user profile (independent of other users/readers)
or more specific on the reading history of a user.
Let's say a specific user likes to read articles about cycling and
international politics and the content management system is saving the
URL history of all the articles which have been read by this specific user.
When the editorial stuff is creating new articles/stories, then the
system should make recommendations to this user when she/he is getting
back online or also when a new story has been created, then the
recommender should check whether this new story would be good fit/match
for this particular user and the system should send a notification.
I guess developing such a recommender is possible with Mahout, but since
I am new Mahout, I would appreciate any pointers to examples which are
similar to the functionality described above.
I am currently looking at the examples shipped with Mahout
https://cwiki.apache.org/confluence/display/MAHOUT/RecommendationExamples
but if I understand correctly these are based on what other people liked
and not what the person itself only liked,
or do I misunderstand?
Thanks for your help
Michael
