Liveramp, Inc.

Amresh Mohanlal

W Dwayne Collins

Pavan Roy Marupally

Dwayne W Collins

A system and method for the creation of household links (HHLs) associates each household with particular consumers associated with a consumer link (CL) and an address link (AL). The system and method utilize a feedback loop system to maintain persistence of HHLs over time and more accurately resolve HHLs. Top-down and bottom-up clustering methods are applied to the data, and the best results are taken to generate the final association of HHLs with particular ALs and CLs. By more accurately identifying the households associated with particular consumer data, the invention significantly reduces the storage requirements and time required for processing very large consumer data sets.

System and method for improving computational efficiency of consumer databases utilizing household links

A distributed node cluster architecture within a parallel computing environment provides for the association of individuals and households accessing a communications network through multiple electronic communications devices with a particular digital touchpoint or touchpoints used when communicating on the network. The cluster facilitates the determination of a touchpoint when an individual or household name is determined, or, alternatively, the determination of an individual or household when a touchpoint is received. A persistent linkage of digital touchpoints to individuals or households communicates with an entity resolution system executing at the node cluster to track data pertaining to entities, allowing the coordination of touchpoints with such individual consumers or households over time.

Distributed node cluster for establishing a digital touchpoint across multiple devices on a digital communications network

A system and method for the creation of household links (HHLs) associates each household with particular consumers associated with a consumer link (CL) and an address link (AL) in order to more accurately identify consumers who are part of the same household. The system and method utilizes a feedback loop system to maintain persistence of HHLs over time and more accurately resolve HHLs from information ingested from multiple files containing consumer information. Both point-in-time (PIT) and temporal data are used. Top-down and bottom-up clustering methods are applied to the data, and the best results are taken to generate the final association of HHLs with particular ALs and CLs. By more accurately identifying the households associated with particular consumer data, the invention significantly reduces the storage requirements and time required for processing very large consumer data sets, allowing, for example, processing of such data on standard desktop computers.

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Conway, AR, United States of America

Amresh Mohanlal