RWTH Aachen University
In this paper, the authors describe details of their approach to the RecSys challenge 2014: user engagement as evaluation. The challenge was based on a dataset, which contains tweets that are generated when users rate movies on IMDb (using the iOS app in a smartphone). The challenge for participants is to rank such tweets by expected user interaction, which is expressed in terms of retweet and favorite counts. During experiments they have tested several current off-the-shelf prediction techniques and proposed a variant of item biased k-NN algorithm, which better reflects user engagement and nature of the movie domain content-based attributes.