Microsoft Corporation
SCALING WORKLOADS USING STAGING AND COMPUTATION PUSHDOWN

Abstract:

In some embodiments, a computer system generates offline a viewer embedding for a user of an online service based on a viewer portion of a scoring model using viewer features stored in a data source in association with a profile of the user, generates offline candidate embeddings for recommendation candidates by a key-value store based on a recommendation portion of the scoring model using features of the recommendation candidate stored in the key-value store, pushes the viewer embedding to the key-value store, generates online pairwise scores for recommendation candidates by the key-value store based on a pairwise portion of the scoring model using the viewer embedding and candidate embeddings, generates ranking scores for the recommendation candidates based on the scoring model using the embeddings and the pairwise scores, and causes recommendation candidates to be displayed on a device of the user based on the corresponding ranking scores.