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Abstract：
Job mobility is common in modern society, especially in the industry of information and communication technology. Job mobility prediction is valuable both for employees and employers. For the sake of lacking appropriate and sufficient records of job mobility, the traditional methods meet a significant challenge in job mobility prediction. Fortunately, the emerging professional social network provides a large amount of users＇ career histories, which can alleviate this problem. In this paper, we collect relevant data from LinkedIn, and analyze the temporal and spatial characteristics to model the job mobility pattern. We propose an approach to predict the company size and position for the next job by using various features, such as the position, duration, and size of previous companies, education degree, etc. The experimental results verify the proposed approach with the accuracy up to 72% and 74% in terms of next company size prediction and next position prediction respectively. © 2016 IEEE.
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Year： 2016
Page： 1668-1675
Language： English
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SCOPUS Cited Count： 2
ESI Highly Cited Papers on the List： 0 Unfold All
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30 Days PV： 2
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