Personalized fusion recommendation for scientific research resources in universities
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Abstract:
To meet the diversified personalized service needs of teachers and students for scientific research resources in universities, a personalized service system for university scientific research resources was designed (PSRSS for short). Firstly, the personalized service needs of users for research resources were comprehensively analyzed. Then, the architecture of multiengine fusion recommendation system was designed with the data layer, the recommendation computing layer which integrates multiple recommendation strategies, and the application presentation layer. Different recommendation algorithms were compared and the selected algorithms were optimized in accordance with the different recommendation scenarios. Next, the user model and scientific research resource model were constructed. Finally, the Top-N recommendation based on the popularity of research resources, similarity of resource content and collaborative filtering of similar users was implemented. The proposed system improves the experience of teachers and students in obtaining scientific research resources and provides new ideas for the development of the personalized service system for scientific research resources in universities.
