Reliable Feedback from Clicking Behavior in Adaptive WWW Search [1/11]

Опубликовано 6 сентября 2016, 5:37

A central goal of information retrieval is the design of functions that rank documents according to their relevance to a query. In this talk, we present an approach to automatically learning such ranking functions. We show that clicking behavior, which unlike hyperlink structure reflects the entire user population, can provide abundant and accurate training data for this learning task. To establish the relationship between clicking behavior and the relevance of a page, we conducted an eye-tracking study. The study shows that a particular interpretation of clickthrough data provides reliable feedback. In particular, clicks accurately indicate relative feedback of the kind for