brain of mat kelcey
brutally short intro to collaborative filtering
March 18, 2010 at 08:38 PM | categories: recommendations, brutally short intro, data mining | View Comments
my favourite recommendations system is the collaborative filter; it gives good resultsand is easy to understand and extend as required.it works on the intuition thatif i like coffee, chocolate and ice creamand you like coffee and chocolateyou might also like ice creamso we need a little bit of terminology; users (me and you), items (coffee, chocolate and ice cream)in a user based collaborative filter the process isto calculate recommendation for user1 for each other user (user2) calculate user_similarity_score between user1 and user2 (0 -> 1 value ) if the user_similarity_score is non zero for each item user2...
old projects...
- latent semantic analysis via the singular value decomposition (for dummies)
- semi supervised naive bayes
- statistical synonyms
- round the world tweets
- decomposing social graphs on twitter
- do it yourself statistically improbable phrases
- should i burn it?
- the median of a trillion numbers
- deduping with resemblance metrics
- simple supervised learning / should i read it?
- audioscrobbler experiments
- chaoscope experiment