Abstract
Human resources big data has a wide distribution range, a large amount of data and a variety of data types. Aiming at the problem of low integration of human resources raw data, an intelligent push method of human resources big data based on wireless social network is proposed. Combined with wireless social network, the human resources data is integrated and mined, and the human resources data is preprocessed to build an OAP data warehouse; then a human resources recommendation algorithm combined with the wireless social network latent semantic model is proposed. Behavior, mining the potential job characteristics of job seekers, and then realize the intelligent push and matching of human resources big data. The test results show that the intelligent push method of human resources big data based on wireless social network proposed in this study has a significantly better recall rate than the traditional single latent semantic model and deep forest algorithm, and effectively improves the integration degree and push efficiency of human resources raw data.
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