HotelRec: a Novel Very Large-Scale Hotel Recommendation Dataset
Table 4: Evaluation of rating prediction in terms of Mean Square Error (MSE) and Root Mean Square Error (RMSE).
['[EMPTY]', '[BOLD] Models', 'MSE', 'RMSE']
the root mean square error (RMSE). Surprisingly, we observe that the neural network TransNet and its extension perform poorly in comparison to the matrix factorization model HFT and the simple Mean baselines. Although TransNet learns a user and item profile based on the most recent reviews, it cannot capture efficiently the interaction from these profiles. Moreover, the additional collaborative-filtering component in TransNet-Ext seems to worsen the performance, which is consistent with the results of \newcitemusat2013recommendation; in the hotel domain, the set users who have rated the same hotels is sparser than usual recommendation datasets.