Company user information protection of e-Commerce platform based on a credit assessment system

The amount of good responses from e-buyers is used by the e-commerce website to determine an e-commerce seller's rating. Furthermore, there is frequently a discrepancy between the e-buyer information evaluation and the assessment outcome. Because the assessment result contains specific subjective criteria, the e-seller star rating, which is only decided by the number of positive remarks, cannot entirely represent the e-seller credit quantity. As a result, the shoe e-seller on the Taobao e-commerce website will be used as an example to assess e-seller credibility.Nine evaluation indices are chosen, such as customer satisfaction, product information, services, market share, and so on, incorporated in assessment details. Python is used to retrieve 153 examples of shoes from e-commerce sites. An e-Commerce platform based on a credit assessment system is proposed in this article. It classifies shoe e-sellers using the fuzzy c-means (FCM) grouping technique, and it calculates their credibility rank based on the categorization outcome. The credit rank of an e-seller is matched to their rating level, and the variation is calculated.Secondly, it employs the FCM method to assess the relationship between each index and credibility to identify the key variables influencing e-seller credit. The above-mentioned e-seller credibility evaluation system might serve as a point of comparison for e-buyers when making a purchasing choice.