Techniques to predict attributes for a user or user group are described. User profiles and connections to other users are analyzed to determine user groups such as a household. Clusters are formed based on matching attributes of similar user groups. Available databases are queried using the user group identifiers to obtain a group-wide attribute value, e.g., household income, for a subset of user groups of a cluster. The obtained values are used to predict missing attribute values that were not found in the database, after adjusting for variations between user groups, such as a number of users in the group. User/group profiles are updated with the predicted attribute values. The predicted attribute values are utilized to customize content delivery to users.
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Anonymous, "Attribute Prediction Based On Online Connections", Technical Disclosure Commons, (December 28, 2018)