Abstract: Various of the disclosed embodiments present systems and methods for generating consolidated job postings from disparate originating sources and formats. Applying an Extraction Transform Load (ETL) framework to the incoming data, a parallel and asynchronous as well as scalable approach to distributing job posting information is presented. “Extraction” may involve the recognition of salient information in the disparate formats (e.g., in employment listings on company webpages). During “transformation”, the information may be reformatted into a universal format or into a format suitable for use at a given destination system. During “loading”, the reformatted data may be supplied to a suitable destination system, e.g., the Application Programming Interface (APIs) of a job board system. Applications in related domains and various optimizations are also discussed.

Abstract: Various of the disclosed embodiments present systems and methods for generating consolidated job postings from disparate originating sources and formats. Applying an Extraction Transform Load (ETL) framework to the incoming data, a parallel and asynchronous as well as scalable approach to distributing job posting information is presented. “Extraction” may involve the recognition of salient information in the disparate formats (e.g., in employment listings on company webpages). During “transformation”, the information may be reformatted into a universal format or into a format suitable for use at a given destination system. During “loading”, the reformatted data may be supplied to a suitable destination system, e.g., the Application Programming Interface (APIs) of a job board system. Applications in related domains and various optimizations are also discussed.

Abstract: Various of the disclosed embodiments present systems and methods for visualizing social network information to identify correlations between employees and their peers. In some embodiments, the system may receive a list of candidates for the position and a list of employees well-suited to their existing positions. The system may then consider social network information to identify relations between the employees and the candidates as relates to the various job positions. The relations may be identified by applying various functions of differing granularity. Once the relations are identified, the system may present the relations in an edge-node depiction to a recruiter. The recruiter may then use the visualization to inform the next step in their decision process (e.g., identify an employee to recommend candidate peers, identify candidates for interviews, etc.).