Monday, December 5, 2011
Sunday, December 4, 2011
In the Content-Based Recommending, recommendations are based on information
on the content of items rather than on other user's opinions.
We can recommend to users with unique tastes.
We will be able to recommend new and unpopular items.
The Collaborative filtering follow the following steps:
Weight all users with respect to similarity with the active user.
Select a subset of the users (neighbors) to use as predictors.
Normalize the ratings and compute a prediction from a weighted combination of the selected neighbors ratings.
Present items with highest predicted ratings as recommendations.