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E-commerce Recommendation Algorithm Based on Big Data Analysis and Genetic Fuzzy Clustering

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DOI: 10.23977/ferm.2023.060904 | Downloads: 21 | Views: 401


Jiwang You 1


1 Nanjing University Business School, Nanjing, Jiangsu, China

Corresponding Author

Jiwang You


With the continued expansion of the EC scale, personalized recommendation technology is widely used. However, traditional referral systems cannot meet current data processing needs, and the presence of highly powerful big data analytics capabilities is a fundamental prerequisite for new personalized referral systems. The paper focuses primarily on EC recommended algorithm research based on big data analysis and fuzzy clustering gene analysis. Based on the literature data, understand the basic theoretical issues related to EC boosting calculations and analyze the methods of genetic fuzzy group analysis. The EC promotion algorithm is designed and the designed algorithm is tested. In conclusion, the algorithm given in this work has a low MAE like the other two algorithms, so its configuration quality is high.


Genetic Algorithm, Fuzzy Clustering, Recommendation Algorithm, EC


Jiwang You, E-commerce Recommendation Algorithm Based on Big Data Analysis and Genetic Fuzzy Clustering. Financial Engineering and Risk Management (2023) Vol. 6: 28-33. DOI:


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