Abstract: Training programs (e.g., for training a user to use a company's products) may be flexibly benchmarked by first identifying user interactions with one or more of the training programs and converting the user interactions into user activity data objects associated with user identifiers. The user activity data may then be made anonymous by removing the user identifiers from the data before examining the data. The anonymized user activity data may then be aggregated with respect to each of the training programs. A benchmark model for evaluating the training programs may then be determined based on a flexible benchmark schema of selectable benchmark metrics for evaluating aspects of the training programs. Benchmarks may then be calculated for each of the training programs based on the aggregated user activity data and the benchmark model. The benchmarks may then be displayed and/or analyzed to generate insights or suggestions for improving the training programs.

Abstract: A system and method include processing devices to implement an automated synchronization system for an intelligent talent platform, the automated synchronization system including one or more remote system adapters each coupled to a corresponding remote system, to retrieve one or more first data objects containing information relating to managing talents, a synchronization handler to obtain, based on identification features of the one or more first data objects, one or more second data objects from a storage device associated with the intelligent talent platform, calculate a consistency score based on values in the one or more first data objects and values in the one or more second data objects, and responsive to determining that the one or more first data objects comprise modifications from the one or more second data objects based on the consistency score, determine priority values associated with the modifications to the one or more first data objects.

Abstract: A system and method include one or more processing devices to obtain a job description comprising requirements for a job, identify, based on at least one requirement in the job description, qualified talent profiles that each characterizes a corresponding qualified person for the job, calculate, by applying a deep neural network to each of the qualified talent profiles, embedding vectors, determine a cluster of embedding vectors based on a similarity distance metric, determine linguistic units in a group of the qualified talent profiles, and determine implied traits based on traits explicitly specified in the job description and common traits among the group of qualified persons.

Abstract: Techniques for providing control selection and analysis of Search Engine Optimization (SEO) activities for web sites for web service providers are disclosed. In some embodiments, a system, process, and/or computer program product for providing control selection and analysis of SEO activities for web sites includes selecting a first plurality of web pages associated with a web site for use in a control group of web pages for an experiment; selecting a second plurality of web pages associated with the web site for use in a test group of web pages for the experiment; canonicalizing the control group of web pages and the test group of web pages; and performing the experiment to determine a performance of the test group of web pages relative to the control group of web pages. For example, the test group of web pages can be configured with an SEO content improvement activity.