Research on the Accurate Recommendation Management System for Employment of College Graduates on Hadoop

Chen, Zhigao; Liang, Wenqian; Gao, Xiong; Zhou, Zhijian; Wu, Meng

doi:10.1109/bigdia.2019.8802855

Cited by 4 publications

(2 citation statements)

References 4 publications

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“…In this context, how to improve the employment competitiveness of graduates has become a topic for colleges and universities to think and explore. The employment of college graduates has always been a common concern and research issue of the government, colleges and society, and colleges and universities are actively exploring effective ways to improve the employment competitiveness of graduates under the new situation [1][2].…”

Section: Introductionmentioning

confidence: 99%

Research on the Precise Employment and Education Training Mode of Engineering Colleges under the Internet Big Data

2023

avte

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The mode of employment education in colleges and universities has always been the focus of employment work in colleges and universities in China, but there are some problems in the construction of employment education mode in colleges and universities at present. Taking engineering colleges as an example, this paper explores the mode of employment education in colleges and universities under the big data of the Internet, analyzes the factors affecting its development, and puts forward solutions to the existing problems. By constructing the dual-subject education mode of "major+employment", students' training is combined with career planning. Guided by industry demand and centered on the improvement of students' ability, a set of dual-subject education system of "major+employment" and dual-subject education mode of "career planning+enterprise demand" are constructed, which combines students' personal development with career planning to achieve the purpose of improving students' employability and enhancing their professional competitiveness.

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Section: Introductionmentioning

confidence: 99%

Research on the Precise Employment and Education Training Mode of Engineering Colleges under the Internet Big Data

2023

avte

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“…For the comprehensive application of algorithms, Li N [6] implemented a comprehensive evaluation system for college students based on the web, realizing standardized storage and data analysis of student information. With the data of previous graduates' graduation destinations as the actual reference, Shen D [7] used the integrated classification algorithm to predict the graduation destination for students, and performed employment prediction for students according to their actual situation and previous graduates' employment situation, so the recommendation system is of more reference value for recent graduates. Liu X X [8] analyzed the traditional collaborative filtering recommendation algorithm based on users, put forward a new hybrid algorithm, and compared the application results of the two algorithms in the employment recommendation system of higher vocational colleges, confirming that the improved hybrid algorithm is more suitable for the employment recommendation system of higher vocational colleges and has improved the accuracy of similar students' recommendation.…”

Section: Introductionmentioning

confidence: 99%

Employment Information Recommendation Model Based on Improved Density Clustering

Duan¹,

Wang²,

Guo³

et al. 2023

Proceedings of the 2nd International Conference on Internet Technology and Educational Informatization, ITEI 2022, December 23-

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Given employment difficulties and low employment quality of college students under the background of higher vocational enrollment expansion, an employment information recommendation model based on improved density clustering was designed. A weighted user similarity calculation method based on professional similarity, job intention similarity, and professional ability similarity was given, and the quantitative analysis process of professional ability was optimized. Considering that high-density samples are closely surrounded by low-density samples, a new density clustering algorithm was proposed to improve the accuracy of employment recommendations. The practice has proved that this model can effectively mine students' employment information, and reduce the iteration times of the clustering algorithm, accompanied by high information retrieval integrity and good personalized employment recommendation performance.

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Collaborative Filtering Recommendation Algorithm and Recommendation System for College Students’ Employment

Wang,

Sun,

Jingyu

et al. 2024

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Research on the Accurate Recommendation Management System for Employment of College Graduates on Hadoop

Cited by 4 publications

References 4 publications

Research on the Precise Employment and Education Training Mode of Engineering Colleges under the Internet Big Data

Research on the Precise Employment and Education Training Mode of Engineering Colleges under the Internet Big Data

Employment Information Recommendation Model Based on Improved Density Clustering

Collaborative Filtering Recommendation Algorithm and Recommendation System for College Students’ Employment

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