Research on personalized recommendation of employment and entrepreneurship platform based on multi-objective hybrid recommendation algorithm
With the increasing demand for employment and entrepreneurship of college students,the traditional multi-objective algorithm cannot give personalized recommendation according to the characteristics of each student group.Therefore,in order to pro-vide personalized employment and entrepreneurship recommendations for college students,the improved OR-tree Algorithm(GA-MORA)based on Genetic Algorithm is studied,and a personalized employment and entrepreneurship recommendation model for students is designed.The model simulates the process of biological evolution to find the optimal solution,and finally generates person-alized recommendation results.The results show that through the performance evaluation of GA-MORA algorithm in the recommenda-tion of employment and entrepreneurship platform,it is found that the algorithm has excellent performance in diversity and other indi-cators.In addition,the study also found that the degree of career preference of different student groups is affected by various factors such as personal interest,professional attributes,regional familiarity and economic factors.The regional familiarity index of female students is 0.8,which is more concentrated than that of male students.It can be seen that female students are more likely to choose more familiar places for employment.To sum up,the algorithm model of this study is superior,which is conducive to providing a reli-able scheme for college students'employment and entrepreneurship.
multi-objective algorithmgenetic algorithmemployment and entrepreneurship platformpersonalized recommen-dationoccupational preference
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