US Patent 10521824 System and method for personalized content recommendations

Identifying personalized content recommendations for users in an electronic environment is disclosed. User data comprising information relating to web-based content consumption of multiple users is collected. Multiple user cluster types associated with one or more interest categories are established. A feature vector is generated for each user for each of the multiple user cluster types. Based on the generated feature vectors, the user are grouped into multiple clusters. A grade is generated for each of a plurality of candidate recommendations for each of the clusters. Based on the generated grades, one or more personalized content recommendations for each of the clusters are identified.