Computer Science

Computer Science ›› 2024, Vol. 51 ›› Issue (2): 47-54.doi: 10.11896/jsjkx.221200149

• Database & Big Data & Data Science • Previous Articles     Next Articles

Fusion Model of Housekeeping Service Course Recommendation Based on Knowledge Graph

ZOU Chunling, ZHU Zhengzhou   

  1. School of Software and Microelectronics,Peking University,Beijing 102600,China
  • Received:2022-12-26 Revised:2023-04-17 Online:2024-02-15 Published:2024-02-22
  • About author:ZOU Chunling,born in 1991,master.Her main research interests include construction of domain knowledge map and recommendation model.ZHU Zhengzhou,born in 1979,Ph.D,associate professor.His main research interests include personalized recommendation and educational big data in big data environment.

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Abstract: Housekeeping service practitioners’ demand for online learning of housekeeping service courses has increased.How-ever,the existing online learning websites of housekeeping service courses have few resources,insufficient systematic courses and no course recommendation function,which makes the threshold of online learning for housekeeping service practitioners become higher.Based on the analysis of the existing online learning websites of housekeeping service courses,this paper proposes to construct the knowledge graph of housekeeping service courses,and integrates the knowledge graph of housekeeping service courses with the recommendation algorithm,and designs an R-RippleNet recommendation model for housekeeping service courses that combines the rules of deep learning technology and the water-wave preference propagation.The objects used by R-RippleNet model include old students and new students.The old students make course recommendation based on the water wave preference propagation model,while the new students make course recommendation based on the rule model.Experimental results show that the AUC value of old trainees using R-RippleNet model is 95%,ACC value is 89%,F1 value is 89%,the mean of the overall accuracy rate of new trainees using R-RippleNet model is 77%,the mean of NDCG is 93%.

Key words: Fusion model, Knowledge graph, Housekeeping service, Course recommendation, Graph database

CLC Number: 

  • TP391
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