An Improved K-means Algorithm for Supplier Evaluation and Recommendation of Purchase and Supply Platform

Abstract

Abstract Aiming at the problem of supplier evaluation and selection in B2B e-commerce, a supplier evaluation and recommendation method based on improved k-means algorithm is proposed. Firstly, this paper analyzes the supplier evaluation and recommendation ideas based on the purchase and supply platform, and proposes the data mining algorithm ideas of clustering analysis and AHP evaluation; secondly, K-means algorithm is proposed based on the data mining model, and the algorithm is optimized according to the data characteristics of the purchase and supply platform; finally, taking the business data of the industrial product purchase platform of the volume purchase network as an example, not only the effectiveness of the algorithm is verified, but also the clustering effect of the algorithm is good and the calculation speed is fast, which provides a practical and effective supplier evaluation and recommendation method for B2B trading website.