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利用大规模在线产品评分网络进行客户定位的模型式协同聚类AI 解读

Given the widely available online customer ratings on products, the individual-level rating prediction and clustering of customers and products are increasingly important for sellers to create targeting strategies for expanding the customer base and improving product ratings.However, the massive missing data problem is a significant challenge for modeling online product ratings.To address this issue, we propose a new co-clustering methodology based on a bipartite network…

高维成分数据的稳健协方差估计及销售数据应用AI 解读

Compositional data arises in a wide variety of research areas when some form of standardization and composition is necessary. Estimating covariance matrices is of fundamental importance for high-dimensional compositional data analysis. However, existing methods require the restrictive Gaussian or sub-Gaussian assumption, which may not hold in practice. We propose a robust composition adjusted thresholding covariance procedure based on Huber-type M-estimation to estimate the…