Big data-based occupational interest prediction method and device, equipment and storage medium

Abstract

The invention provides a big data-based occupational interest prediction method and device, equipment and a storage medium. The occupational interest prediction method comprises the following steps: when an occupational interest prediction instruction is received, collecting attribute data of a predicted person; carrying out semantic matching on the attribute data by using a BERT algorithm to obtain behavior data of the predicted person so as to ultilize the collected data fully and reasonably; further fitting a pre-trained prediction model based on the behavior data, and when the prediction model is adjusted, outputting a fitting score, outputting the fitting score in the form of a score, so as to enable the prediction result to be more interpretable, sorting the fitting score to obtain asorting result, and predicting the occupational interest according to the sorting result, thereby realizing intelligent prediction of the occupational interest based on data processing.

Description

technical field [0001] The present invention relates to the technical field of data processing, in particular to a big data-based career interest prediction method, device, equipment and storage medium. Background technique [0002] Career interest is one of the key factors affecting a person's life. Studies have shown that in middle school and university education, career planning should focus on the exploration of the dimension of interest; Dr. Kai-Fu Lee once said: "95% of successful people choose to engage in the work or career they are interested in. And most of them don't regard making money as their goal in life, what they love is their hobby." [0003] Every year, more than 8 million people in the world improve job satisfaction through career assessment, realize their wishes, and then move towards a happy life. It can be seen how important it is to explore career interests. [0004] However, at present, the popularity and attention of career interest exploration is...

AI Technical Summary

Problems solved by technology

[0005] (1) The process is cumbersome and requires high requirements for the predictee

[0006] Although Holland's Self-Directed Search and MBTI occupational personality test are recognized classic occupational interest testing methods, the implementation process is very cumbersome and requires the predictee to have a good self-awareness, and this is a very strict condition

[0007] (2) The results are not objective and difficult to interpret

[0008] The current career interest test often directly gives a series of recommended results, but we don't know which ones are more suitable for us, so in the end we still inevitably need to find professionals to evaluate and interpret, which directly leads to career problems. The high cost and difficulty of popularizing interest assessment

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