Abstract
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.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Anonymous, "Attribute Prediction Based On Online Connections", Technical Disclosure Commons, (December 28, 2018)
https://www.tdcommons.org/dpubs_series/1824