Sentiment Analysis and Personalized Recommendations Based on JD.com Reviews

Authors

  • Yutong Zhang

DOI:

https://doi.org/10.54097/fbem.v4i3.1048

Keywords:

Natural language processing, Sentiment analysis, Personalized recommendation, JD.com review.

Abstract

The general big data personalized recommendation is based on the number of times or the length of time users click on a related content, but in many cases, these cannot be the most direct basis for accurate recommendation, and there may be cases such as wrong clicks by users. These factors and a large number of related products or articles recommended to users may cause users' disgust. This article conducts sentiment analysis on JD.com reviews as an example, obtains the user's likes and dislikes, and then makes accurate personalized recommendations, so that a greater understanding of preferences can improve the effect of recommendations, and more accurate personalized recommendations.

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References

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Published

31 July 2022

How to Cite

Zhang, Y. (2022). Sentiment Analysis and Personalized Recommendations Based on JD.com Reviews. Frontiers in Business, Economics and Management, 4(3), 25–28. https://doi.org/10.54097/fbem.v4i3.1048

Issue

Section

Articles