Recommendation Browser has been developed to investigate recommendations users receive in Lenskit framework. The graphical user interface looks as follows:
The data is generated based on four files:
item.csv - recommendations user received (generated by Lenskit)
test.0.csv - test user data (generated by Lenskit)
train.0.csv - train user data (generated by Lenskit)
content.dat - content data (generated by developer)
The big table in the second part of the screen shows training data and recommendations provided by a recommendation algorithm. The table is divided into two parts: training data and recommendations. The table includes the following columns: ItemId, Rating, Score, content features.
Currently, the project is raw, but it might be helpful for recommender system researchers.
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