Discovering Association Between Talent Flow and Socio- Economic Features in Corporate Companies

Abstract

organizations, regions and industries. Talent flow estimation is utilized in human resource planning, brain drain monitoring and future workforce forecasting tasks. The online resume data are analyzed to extract features historical talent flow, dynamic attributes and static profiles. The company stock price movement and talent flow correlations are extracted using the DJTN and share market data. The multiple data sources are derived from the Dynamic Job Transition Network (DJTN). The Deep Sequence Prediction (DSP) model integrates multiple data sources and multi step forecasting of future talent flow. The Recurrent Neural Network (RNN) is used in the deep sequence prediction model. In this paper the Optimized Recurrent Neural Network (ORNN) is constructed to handle multiple input data sources for the prediction process.

Key words:  Talent flow analysis, Dynamic Job Transition Networks (DJTN), Deep Sequence Prediction (DSP), Recurrent Neural Network (RNN) and Optimized Recurrent Neural Network (ORNN).