How we can run a recommendation system on Apache Mahout based on user liking or browsing history? In short on a content based websites 95% traffic by non logged in users and they will come via search engine. They only way we can unique them by using IP. Is there anyway on Apache Mahout where we can find out the similar browsing behavior of users and recommend relevant content?
A simple but probably pretty effective starting point would be to use the IP address as a user ID (construed as a long), and use pages liked or browsed as items. I would start by even forgetting about assigning ratings.
Then use GenericBooleanPrefItemBasedRecommender in Mahout plus a suitable similarity metric like LogLikelihoodSimilarity on top of whatever DataModel suits you, and you're pretty much there.