Abstract: Computer systems and methods generate a cluster chart for HR-related documents. A host computer data center comprises a database for electronically storing HR-related documents, a web server, and a programmable computer device. The programmable computer device is programmed to determine clusters of prevalent terms in a collection of HR-related documents in the database. The collection of HR-related documents from which the clusters are generated is identified based on search criteria submitted from a client computer device. The clusters of prevalent terms in the collection can be determined using a clustering algorithm employing algebraic transformations of a term-document matrix generated from the collection of HR-related documents. The programmable computer device is also programmed to assign each of the HR-related documents in the collection to one or more of the determined clusters, and to generate a chart graphically showing the clusters. Each cluster in the chart has a characteristic (e.g.

Abstract: Computer-based systems and methods for prioritizing a list of job candidates for a job opening(s) with a hiring firm use the Random Forest algorithm, in which a number of decision trees are generated and the job candidates' respective probabilities of being the right fit for the hiring firm and for the position(s) are computed using the forest of decision trees. The job candidates may then be ranked according to their computed hiring probability. Non-conventional variables can be used, such as social media-related variables and external industry variables, such as the candidates' driving records. Other non-conventional variables that can be used include results from a personality or behavior assessment, results from a third-party skill assessment, and performance evaluations for prior projects or jobs of the candidates.