For the second week, I first read some materials on computing interpolation weights for neighborhood-based collaborative filtering. There are three methods I planned to implment: average interpolation, similarity-based interpolation, and regression-based interpolation. So far I have implmented
SimilarityInterpolation, and I am currently working on
RegressionInterpolation. As for rating normalization, I merged codes of refactored CF class (thanks to Haritha for the refactoring work), and I am working to solve some issues that occur after the merge.
For the third week, I am going to modify methods in CF to use policy-design for weights interpolation and neighbor search, add
RegressionInterpolation. After that I will do the remaining work of rating normalization.
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