Abstract
Query logs record past query sessions across a time span. A statistical model is proposed to explain the log generation process. Within a search engine list of results, the model explains the document selection - a user's click - by taking into account both a document position and its popularity. We show that it is possible to quantify this influence and consequently estimate document "un-biased" popularities. Among other applications, this allows to re-order the result list to match more closely user preferences and to use the logs as a feedback to improve search engines. © Springer-Verlag Berlin Heidelberg 2006.
Cite
CITATION STYLE
Dupret, G., Piwowarski, B., Hurtado, C., & Mendoza, M. (2006). A statistical model of query log generation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4209 LNCS, pp. 217–228). Springer Verlag. https://doi.org/10.1007/11880561_18
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