Survival analysis of click logs

Si-Chi Chin, W. Nick Street

Abstract: Click logs from search engines provide a rich opportunity to acquire implicit feedback from users. Patterns derived from the time between a posted query and a click provide information on the ranking quality, reflecting the perceived relevance of a retrieved URL. This paper applies the Kaplan-Meier estimator to study click patterns. The visualization of click curves demonstrates the interaction between the relevance and the rank position of URLs. The observed results demonstrate the potential of using click curves to predict the quality of the top-ranked results.