Method and apparatus for presenting a sequence of target objects to a target user

Abstract

The embodiment of this specification provides a method and device for displaying target object sequences to target users. The method includes: inputting each interaction feature vector into the reordering model according to the initial ranking, the reordering model includes an encoder and a decoder, and the encoder determines the target object The global attention of each target object in the sequence and the first target object, and encode the first target object into a first latent feature vector according to the global attention; determine the partial target in the target object sequence centered on the first target object The local attention of the object and the first target object, according to the local attention, the first target object is encoded into the second latent feature vector; the first latent feature vector and the second latent feature vector are weighted and summed to obtain the comprehensive latent feature vector ; The decoder determines the reordering of each target object according to each integrated latent feature vector; and displays the target object sequence to the target user according to the position of each reordered target object. Able to maximize user feedback.

Description

technical field [0001] One or more embodiments of this specification relate to the computer field, and in particular to a method and device for presenting target object sequences to target users. Background technique [0002] At present, the target object sequence is often displayed to the target user to recommend multiple target objects in the target object sequence to the target user. In order to achieve a specific business goal, it is necessary to filter out a large number of target objects that the user may be interested in Multiple target objects, forming a target object sequence by these multiple target objects, and determining the position of each target object when displaying the target object sequence are all performed based on the sorting of the target objects. [0003] In the prior art, when sorting the target objects, it is usually sorted according to the correlation between each target object and the target user from high to low. The above correlation reflects t...

AI Technical Summary

Problems solved by technology

[0003] In the prior art, when sorting the target objects, it is usually sorted according to the correlation between each target object and the target user from high to low. The above correlation reflects the target user's preference for the target object. When displaying target object sequences, it is often impossible to maximize user feedback, for example, to maximize the target user's click rate for each target object, or to maximize the conversion rate, etc.

Images