A method includes receiving a request associated with a first attribute and a criterion, the request representative of an opportunity for employment, each first attribute representative of a qualification associated with the opportunity for employment, the criterion representative of a target affiliation; querying a database to identify a record including a second attribute satisfying the first attribute associated with the request and including a third attribute satisfying the criterion associated with the request, the first attribute included in the record having been determined based on other information in the record; and serving, to a computing device operated by a user associated with the identified record, a network resource providing the user with access to information about the request.

A method, computer program product, and computer system for identifying, by a computing device, a user profile of a plurality of user profiles associated with a profession, wherein the user profile may be associated with a user. The user profile may be analyzed. It may be determined that the user is eligible to receive an assessment based upon, at least in part, analyzing the user profile. The assessment may be administered to the user. Answers for the assessment provided by the user may be recorded. A score for the assessment may be generated based upon, at least in part, the answers for the assessment provided by the user. A recommended course of a plurality of courses for the user to receive may be identified based upon, at least in part, the score for the assessment.

By executing a natural language processing model on a set of natural language text describing a first engagement, a set of characteristics of the first engagement is generated. By executing the natural language processing model on a set of natural language text describing a future engagement, a set of characteristics of the future engagement is generated. The first engagement is determined to be above a threshold similarity with the future engagement. Using the skillset used in performing the first engagement, a required skillset of the future engagement is forecasted. By executing the natural language processing model on a set of natural language text describing a current skillset, a set of characteristics of the current skillset is generated. Using the required skillset of the future engagement and the set of characteristics of the current skillset, a learning path is generated.

By executing a natural language processing model on a set of natural language text describing a first engagement, a set of characteristics of the first engagement is generated. By executing the natural language processing model on a set of natural language text describing a future engagement, a set of characteristics of the future engagement is generated. The first engagement is determined to be above a threshold similarity with the future engagement. Using the skillset used in performing the first engagement, a required skillset of the future engagement is forecasted. By executing the natural language processing model on a set of natural language text describing a current skillset, a set of characteristics of the current skillset is generated. Using the required skillset of the future engagement and the set of characteristics of the current skillset, a learning path is generated.

Systems and methods for assessing the skills of a customer support agent using one or more Artificial Intelligence/Machine Learning (AI/ML) models are disclosed. In at least one embodiment, one or more benchmarks against which the performance of the customer support agent is to be measured are established. The one or more benchmarks may be derived through direct and/or indirect analysis of historical customer service data by an AI/ML benchmark model. In at least one embodiment, data relating to performance of the customer support agent during a customer call is monitored. In at least one embodiment, the AI/ML benchmark model is used to determine one or more benchmark scores identifying whether the customer support agent is meeting the one or more benchmarks.

A method and system is provided for real-time human resource activity impact assessment and real-time improvement. The present application provides a method and system for real-time human resource activity impact assessment and real-time improvement comprises of categorizing activity target parameters in a data set; assigning a real time target to the human resource management (HRM) associate; converting the intangible aspect of the assigned target to tangible aspect; initiating the real time feedback implemented session and generating an alert by HRM associate; receiving the alert and registration by the users for the session ;displaying in session, a real time synchronized feedback window; capturing feedback provided by the users; implementing captured feedback and modifying the session in real time; calculating an activity target achievement score of the session; and computing the activity assessment and improvement by calculating overall target achieved score and ranking the associate based on the computed achieved target parameters.

A comprehensive multi-skilling framework system provides technology tailored for managing and staffing multi-skilled IT professionals. Multi-skill data and proficiencies generated for each individual user are defined, enabled, measured and tracked in the multi-skilling framework. An automated multi-skilling manager receives data that defines technical platforms and a plurality of multi-skill roles within each technical platform. Multiple skills are associated with each multi-skill role and each user is mapped to a multi-skill role. An overall proficiency level that pertains to a user's respective multi-skill role is determined based on multi-skill assessment data for the user. By assigning a multi-skill role to each user and automatically generating a unique proficiency level for each user based on their multi-skill role information, the process of staffing IT projects from large populations of IT professionals is streamlined and conserves processing resources.

System and methods for determining course need based on member data are disclosed. For a respective skill in a list of skills, a server system determines a member interest score in the respective skill. The server system then determines an employer interest score in the respective skill. The server system determines a number of courses available for the respective skill at a server system. The server system generates a content priority score for the respective skill in the list of skills based on the member interest, the employer interest, and the number of skill learning materials associated with the skill.

Methods and systems are disclosed for determining gaps in a user's resume regarding skills or titles for a job, and recommending educational courses to the user based on those gaps. The user's resume is received and analyzed for the user's current set of skills. Various searching methods are used to identify a set of job requisitions based on a user's input query for a job. The user's skills are compared with a set of required skills associated with the set of job requisitions. Educational courses are identified for the skills that are required for the set of job requisitions but are not present in the user's set of skills. The educational courses presented to the user via the search engine. The user's resume can also be ranked relative to other resumes for the skills or titles required for a job.

A process of evaluating the residential clinical performance of a medical resident based upon feedback from evaluators includes generating a number of questionnaires. The questionnaires contain questions related to competency area milestones for the medical resident. E-mails are sent to the medical resident with access codes for the questionnaires. The medical resident then works with an evaluator to treat a patient, the patient receiving healthcare related to a competency area milestone. The medical resident then sends the evaluator an access code for a questionnaire related to the competency area milestone. The evaluator uses the access code to access the questionnaire and answers the questions on the questionnaire. Answers are logged in a database.