Realtime Feedback Using Affinity-Based Dynamic User Clustering

摘要

The disclosure relates in some cases to a technology for selecting one or more promotions to be presented to online customers using Bayesian bandits and affinity-based dynamic user clustering In some embodiments, a computer-implemented method determines a set of offers is determined, and computes affinity scores measuring affinities of users to items included in the offers. The method builds an affinity score distribution for the offers and identifies clusters of affinity scores for the offers using the corresponding affinity score distribution.

主权项

1. A method for multi-modal determination of an offer executable by a computing system including one or more processors and one or more memories, the method comprising:
receiving, using the one or more processors, a set of offers; computing, using the one or more processors, affinity scores measuring affinities of users to items included in the offers; building, using the one or more processors, an affinity score distribution for each of the offers; identifying, using the one or more processors, clusters of affinity scores for each of the offers using the corresponding affinity score distribution; receiving, using the one or more processors, a content request; determining, using the one or more processors, an offer including an item; retrieve, using the one or more processors, user information for user associated with the content request; computing, using the one or more processors, a user affinity score to the item of the offer using the user information; identifying, using the one or more processors, a cluster that the user affinity score belongs to from among a plurality of clusters of affinity scores; retrieving, using the one or more processors, a beta distribution corresponding to a cluster ID of the identified cluster; and generating, using the one or more processors, a response estimate using the beta distribution.