Abstract: To train models, training data is needed. As personal data changes over time, the training data can get stale, obviating its usefulness in training the model. Embodiments deal with this by developing a database with a running log specifying how each person's data changes at the time. When data is ingested, it may not he normalized. To deal with this, embodiments clean the data to ensure the ingested data fields are normalized. Finally, the various tasks needed to train the model and solve for accuracy of personal data can quickly become cumbersome to a computing device. They can conflict with one another and compete inefficiently for computing resources, such as processor power and memory capacity. To deal with these issues, a scheduler is employed to queue the various tasks involved.

Abstract: Disclosed herein are system, method, and computer program product embodiments for linking data records in memory. The system, method, and computer program product includes accessing a first record stored in memory, the first record holding information describing a first person and accessing at least one additional record stored in memory, the additional records holding information describing additional persons. The method continues by parsing the information of the first record and additional record and assigning the parsed information to predefined categories within the respective records. After assigning the information into categories, a similarity score between categorical information in the first record and categorical information of additional records is determined. A category of an additional record is then modified based on the similarity score, so the additional record is associated with the first person.

Abstract: Disclosed herein are system, method, and computer program product embodiments for performing a regression analysis on lawfully collected personal data records. The analysis enables discovery of individuals likely to perform certain actions based on their personal data records and the personal data records and actions of others. The disclosed system, method, and computer program product may process vast quantities of data, including personal data records with thousands of categories and lawfully stored databases with millions of personal data records. Through the regression analysis, the disclosed system, method, and computer program product learn the most relevant categories for predicting an individual's actions based on input data provided by a user. The analysis then analyzes the categories of personal data records stored in a lawfully stored database to predict actions of individuals associated with those records and outputs results to the user.