Application of BiLSTM-CRF Approach and its Application for Better Decisions in Human Resource Management Processes

Recent advances in information technology (IT) have had a profound effect on human resources (HR) procedures and practices. Despite this, there is a dearth of research on its effectiveness, and the studies that have been undertaken have not, in general, assessed how well these new technologies aid firms in attaining their HR goals of attracting, motivating, and retaining personnel. Current systems have limitations, such as being one-way, passive, impersonal, limiting opportunities for human connection, and creating too much physical and intellectual barrier between individuals and enterprises. Data preparation, feature extraction, and model training are the first three stages of the suggested procedure. Normalization is a tool used in the preliminary processing of data. PCA is used to extract features and identify the most informative ones. After feature extraction, the models are trained using BiLSTM-CRF. When compared to the two most common alternatives, BiLSTM and CRF, the proposed technique achieves better performance.

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