Abstract: Technologies for generating relevance-independent position effects estimates for a set of ranked digital items are described. Embodiments include creating an input data set that includes request tracking data and associated activity tracking data. A relevance-independent position effects estimator generates an output data set. An item of the output data set includes user interface position data associated with a pair of adjacently positioned items of the input data set. The user interface position data indicates that a change in user interface activity probability data relating to a change in position between the items of the pair is greater than a change in the user interface activity probability data relating to a difference in the relevance score between the items of the pair. The output data set is stored in a searchable data store. Data from the searchable data store is provided to a downstream service.

Abstract: Technologies for generating relevance-independent position effects estimates for a set of ranked digital items are described. Embodiments include creating an input data set that includes request tracking data and associated activity tracking data. A relevance-independent position effects estimator generates an output data set. An item of the output data set includes user interface position data associated with a pair of adjacently positioned items of the input data set. The user interface position data indicates that a change in user interface activity probability data relating to a change in position between the items of the pair is greater than a change in the user interface activity probability data relating to a difference in the relevance score between the items of the pair. The output data set is stored in a searchable data store. Data from the searchable data store is provided to a downstream service.