Abstract: A computer-implemented method for identifying, among user electronic devices, customer electronic devices associated with genuine customers of organizations, the method being executed by a server, the method comprising: receiving, from a first user electronic device by the server, a first uniform resource locator (URL) of a first user browsing history; generating a first embedding corresponding to the first URL; comparing the first embedding with a template embedding of a plurality of template embeddings, the plurality of template embeddings having been retrieved from a genuity database; and in response to a difference between the first embedding and the template embedding being lower than an embedding difference threshold, adding the first embedding to the genuity database.

Abstract: Machine learning systems for predictive targeting and optimizing engagement are described herein. In various embodiments, the system includes 1) training a first machine learning computer model to generate machine predicted outcomes; (2) determining weights based on the machine predicted outcomes; (3) generating a second machine learning computer model based on the weights; and (4) generating machine learned predictions for candidates.

Abstract: A device may receive assessment scores for a candidate associated with an entity and performance data identifying performance metrics and time periods associated with existing members of the entity. The device may process the assessment scores and the performance data, with an attrition model, to identify attrition scores for the candidate and confidences of the attrition scores, and may calculate a final attrition score based on the attrition scores. The device may process the assessment scores and the performance data, with a performance model, to identify performance scores for the candidate and confidences of the performance scores, and may calculate a final performance score based on the performance scores. The device may calculate an overall score based on the final attrition score and the final performance score, and may perform one or more actions based on the overall score.

Abstract: Automated interfaces with interactive keywords between employment postings and candidate profiles are disclosed. An example system includes a profile database and one or more processors. The one or more processors are configured to identify one or more posting keywords by parsing extracted text of an employment posting, retrieve one or more posting search-terms from a search-term database based on the one or more posting keywords, and generate a list of candidates based on one or more candidate profiles retrieved from the profile database. Further, the one or more processors are configured to present, to the recruiter, an interface that includes a posting section and a candidate section adjacent to the posting section. Further, the one or more processors are configured to typographically emphasize the posting keywords that are associated with the posting search-terms to indicate relationships between the employment posting and the list of candidates.