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Summary of research on recommendation system based on serendipity
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作者 Meng Wei Wang Liting LüMeng 《The Journal of China Universities of Posts and Telecommunications》 EI CSCD 2022年第4期89-105,共17页
Personalized recommender systems provide various personalized recommendations for different users through the analysis of their respective historical data.Currently,the problem of the“filter bubble”which has to do w... Personalized recommender systems provide various personalized recommendations for different users through the analysis of their respective historical data.Currently,the problem of the“filter bubble”which has to do with over-specialization persists.Serendipity(SRDP),one of the evaluation indicators,can provide users with unexpected and useful recommendations,and help to successfully mitigate the filter bubble problem,and enhance users’satisfaction levels and provide them with diverse recommendations.Since SRDP is highly subjective and challenging to study,only a few studies have focused on it in recent years.In this study,the research results on SRDP were summarized,the various definitions of SRDP and its applications were discussed,the specific SRDP calculation process from qualitative to quantitative perspectives was presented,the challenges and the development directions were outlined to provide a framework for further research. 展开更多
关键词 serendipity recommended algorithm recommended diversity filter bubbles evaluation indicators
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