Great talk @Harrie Oosterhuis. One quick question. How do you calculate the the P(o_i = 1 / R, d_i) from the logging data? are we just using some historical data about the "golden triangle". In other words, in real world data it seems difficult to know if an item was observed when there are no clicks below it
Never mind I see it is covered later in the talk. Randomization seems a bit impractical though. Any results from using the "golden triangle" from User research to calculate P(o_i = 1 / i)?
Great talk @Harrie Oosterhuis. One quick question. How do you calculate the the P(o_i = 1 / R, d_i) from the logging data? are we just using some historical data about the "golden triangle". In other words, in real world data it seems difficult to know if an item was observed when there are no clicks below it
Never mind I see it is covered later in the talk. Randomization seems a bit impractical though. Any results from using the "golden triangle" from User research to calculate P(o_i = 1 / i)?