Experian Information Solutions, Inc.

Liveramp, Inc.

Shirish Kumar

Prashant Kumar Sahay

Sanskar Sahay

Anukool Rege

Mervyn Lally

This disclosure relates to data association, attribution, annotation, and interpretation systems and related methods of efficiently organizing heterogeneous data at a massive scale. Incoming data is received and extracted for identifying information ('information'). Multiple dimensionality reducing functions are applied to the information, and based on the function results, the information are grouped into sets of similar information. Filtering rules are applied to the sets to exclude non-matching information in the sets. The sets are then merged into groups of information based on whether the sets contain at least one common information. A common link may be associated with information in a group. If the incoming data includes the identifying information associated with to the common link, the incoming data is assigned the common link. In some embodiments, incoming data are not altered but assigned into domains.

Massive scale heterogeneous data ingestion and user resolution

A computerized method for implementing a matching platform for entities includes a real-time processing layer using real-time linking on an input data stream, and a high-throughput layer linking entities from a batch data source stream. The real-time linking results are stored in a state change store and the high-throughput linking results are stored in a state store. On-demand linking uses the state change store and the state store. A lambda switch ensures that the entity states remain consistent when the on-demand linking switches from an older generation of the state store and the stage change store to a newer generation of the state store and the state change store. These stores are implemented in an entity database that parses queries into instructions and creates an instruction stream to control entity matching.

Data manipulation language parser system and method for entity resolution

In one aspect, a computerized method for implementing a matching platform for entities includes the step of, in a real-time data processing layer, implementing a real-time linking on an input event stream. The method includes storing an output of the real-time linking in a state change store. The method includes the step of, in a high-throughput layer, implementing a high-throughput linking of entities from a batch data source stream. The method includes storing an output of the high-throughput linking of entities in a state store to generate a unified and consistent view of the entities across a different representation of the entities. The method includes implementing an on-demand linking using the state change store and the state store.

Growing community of inventors

Saratoga, CA, United States of America

Shirish Kumar