Before revision:  However, it is unclear whether these sampling strategies are the best choice for candidate generation in recommender system, where we face severe selection bias in the training data with an extremely large candidate set and rich features of various types .
After revision:  However, it is unclear whether these sampling strategies are the best choice for candidate generation in recommender system, where we face severe selection bias in the long run, as it aims to faithfully fit the history records, and (2) suboptimal sampling and inadequate use of item features can lead to inferior representations for the items that are unfairly ignored .