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Social and Drift-Aware Collaborative Filtering

For my CSI 5325 (Introduction to Machine Learning) class, I worked on a project which explored improvement on collaborative filtering by (a) taking into account social data when calculating user similarity and (b) taking into account changes in user similarity over time (for example, two people may like the same Christmas movies and give lots of similar ratings in December, but diverge significantly afterward).

My final report, in PDF format, can be found here.