Optimizing Ranking Systems by Direct Interaction with Users

Harrie Oosterhuis, Maarten Rijke

Research output: Contribution to journalArticlepeer-review


Recommendation has become an important part of our digital lives. When watching a video, doing online shopping, listening to music, or even reading a news article, we are being recommended things to look at next. Similarly, we expect easy-to-use search features everywhere to make our way through online content without effort.

Behind every search or recommendation feature there is a ranking system that decides what items to present and in which order. The quality of such a system has a large impact on the user experience: it is wonderful when you get that perfect music recommendation, or the document you are looking for shows up instantly. For companies it can also mean increased revenue: users stay longer on your website, or find products they want to buy more easily.

Thus it is no surprise that optimizing ranking systems is very important and active area of research. We have recently introduced a novel approach that learns user preferences from their interactions and updates ranking systems accordingly.
Original languageAmerican English
StatePublished - Jul 1 2017


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