Analysis and prediction of computer industry talent demand based on machine learning
LE3 .A278 2022
Master of Science
From the perspective of enterprise and social demand, this research analyzes the characteristics of talent demand in Canadian computer industries by using big data thinking, text analysis and machine learning. Firstly, through crawler technology, we obtained the recruitment information on mainstream Recruitment websites in Canada and developed a standardized collection process. After processing the data, we used IBM Watson Studio to split the text and constructed the skill keyword dictionary to extract the talent demand. In addition, the time series algorithm was used to predict the changes of the computer skill keyword over time and visualize the results. After analyzing the experiment results, it is found that computer science related jobs are changing over time and require new skills to adapt. Finally, based on the analysis results, suggestions and plans for cultivating talents related to computer science are proposed from the perspectives of enterprises, governments and campuses. The governments should pay attention to policy making, campuses and enterprises should strengthen cooperation and create a new talent training model.
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