Replaying live-user interactions in the off-line evaluation of critique-based mobile recommendations

摘要

Recommender systems have emerged as an important part of the solution to the information overload problem facing today's Web users. Combining ideas and techniques from information filtering, user modeling, artificial intelligence, user interface design and human-computer interaction, recommender systems provide users with proactive suggestions that are tailored to meet their particular information needs and preferences. Indeed recommender systems have enjoyed considerable commercial success and continue to play an increasingly important role in many online services, from Amazon and iTunes to Tivo and Last.fm.