Equifax Inc.

Sunit Sivaraj

Rajkumar Bondugula

Marek Ludomir Cyzio

Piyushkumar Patel

Haroon Syed

Khizer Daniyal Syed

Search indexes can be automatically generated and used for expediting searching of a computerized database. For example, a system can access an inquiry dataset that includes relationships between prior inquiries and returned records from a database. The system can then generate a set of Boolean indexes based on the prior inquiries. The system can then identify frequent indexes that occur at least a threshold number of times in the set of Boolean indexes and that have estimated candidate sizes that are less than a threshold size. The system can then select the frequent index with the highest frequency from among the frequent indexes. The selected frequent index can be subsequently used to expedite searching of the database in response to receiving a search query associated with the frequent index from a client device.

Automatically generating search indexes for expediting searching of a computerized database

A unit-classification system receives a data set with identity data objects corresponding to personal identity components. Feature vectors are determined for the identity data objects. A trained classifier model determines, based on a feature vector for each identity data object, whether the corresponding personal identity components are included in a identity component ('IC') category. The unit-classification system generates an IC identification for a first IC category, and associates the IC identification with a first identity data object corresponding to a first personal identity component. The unit-classification system identifies a second identity data object corresponding to a second personal identity component included in the first IC category. The unit-classification system modifies the first and second identity data objects to include the IC identification. Responsive to a request for the IC identification, the unit-classification system can provide a response that indicates the modified first and second identity data objects.

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Alpharetta, GA, United States of America

Sunit Sivaraj