Research on Key Algorithms of Intelligent Recommendation System for Retired soldiers’ Employment Training
Pages 61 - 65
Abstract
In view of the problem that retired soldiers are faced with the choice of hundreds of industries and tens of thousands of positions in the society and can't accurately select appropriate training, based on the analysis of the current recommendation algorithm and its shortcomings, this paper constructs the main process of the intelligent recommendation system for retired soldiers’ employment training, and puts forward a recommendation algorithm integrating professional interest, personal ability, social needs and other factors, An example is given to verify the effectiveness of the algorithm. The research helps to accurately recommend training suitable for their own development for retired soldiers, quickly improve their employment and entrepreneurship ability, and then find a job smoothly.
References
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Pang Honglei. Research on employment, education and training in the resettlement system of retired soldiers in China [D]. Beijing: Institute of foreign affairs, 2019
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Zhang kaizhe. Research on the employment and resettlement of retired soldiers in Liaoning Province [D]. Shenyang: Shenyang Normal University, 2020
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Li Yanyan, Xu Na. Innovative research on promoting the improvement of vocational skills of retired soldiers in Local Higher Vocational Colleges – Taking Wenzhou Vocational College of science and technology as an example [J]. Educational theory and practice, 2018,38 (36): 21-23
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Yu Meihua. Research on movie recommendation algorithm integrating user interest and project relevance [J]. Computer knowledge and technology, 2017,13 (8): 22-24
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Chen Pinghua A collaborative filtering recommendation algorithm combined with association rules [J]. Small microcomputer system, 2016,37 (2): 287-292
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Feng Yali, Yu Ruifang, sun longan, etc. Personalized Learning Resource Recommendation Algorithm in distance training [J]. Computer system application, 2017,26 (8): 212 − 216
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Xin Lili. Case work involved in improving the employment adaptability of retired soldiers [D]. Baoding: Hebei University, 2020
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Published In
November 2021
111 pages
ISBN:9781450390552
DOI:10.1145/3502300
Copyright © 2021 ACM.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 27 January 2022
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- Research-article
- Research
- Refereed limited
Funding Sources
- Hebei Provincial Department of education, key technology research and system development of collaborative distribution of maintenance material
- Hebei Vocational University of Industry and Technology, Application of big data technology in equipment health status assessment
Conference
BDSIC 2021
BDSIC 2021: 2021 3rd International Conference on Big-data Service and Intelligent Computation
November 19 - 21, 2021
Xiamen, China
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