职业生涯规划
认知信息处理
职业投资组合
心理学
职业教育
管理
工程管理
职业发展
医学教育
数学教育
人工智能
计算机科学
教育学
工程类
职业教育
经济
医学
标识
DOI:10.2478/amns-2024-3134
摘要
Abstract The number of college graduates is increasing year by year, and college students’ career planning and employment have always been a high concern of the community. The article describes the specific role of artificial intelligence technology in assisting college students’ career planning and employment guidance and combines WEB technology to construct a college student’s career planning and employment guidance service platform. The information entropy is used to construct the feature importance set of student employment data, and the simple Bayesian algorithm is used to realize the construction of the classification model of student employment service data in combination with the feature importance. On the basis of considering the selection of students’ employment information, the time decay factor is introduced to improve the personalized recommendation algorithm, and the cosine similarity between students’ employment positions is calculated so as to realize the generation of students’ employment service information recommendation. The area of the classification ROC curve of the plain Bayesian model is more than 95%, the classification time for student employment service data is only 5.62ms, and the F1 value of the employment service information recommendation result is 6.03% higher than that of the traditional method. The college students’ career planning and employment guidance service platform was only satisfactory for 31.77% of the students, with the highest satisfaction score of 3.69 for getting information. Relying on artificial intelligence technology can help students make personalized recommendations for employment service information, which can improve the level of career planning and guidance for college students.
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