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Amazon Details Its SageMaker AI Pipeline for Evaluating Marketplace Content

1 reports 1 reporting sources Updated 2 hours ago

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Amazon described a SageMaker AI pipeline that evaluates full snapshots of Marketplace product pages and helps teams improve their quality. It combines scores from a vision-language model with OCR readability signals in a CatBoost classifier. Across 5,478 pages in 10 product categories, the combined model reached 0.94 accuracy and a 0.95 F1 score, compared with 0.80 and 0.84 for a baseline that averaged the scores. The pipeline uses SHAP explanations to inform recommendations. Amazon reported that revised pages gained an average of 1.4 points on a 10-point quality scale.

Generated by AI from reports · Updated 1 hours ago

Latest development11/6 02:06 (UTC+8)
How Amazon Marketplace Evaluates Content Quality with Amazon SageMaker AIAWS Machine Learning Blog

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    How Amazon Marketplace Evaluates Content Quality with Amazon SageMaker AI

    Amazon describes a SageMaker AI pipeline that evaluates full product detail page snapshots by combining Vision-Language Model scores with OCR readability signals in a CatBoost classifier. On 5,478 pages across 10 product categories, the fused model reached 0.94 accuracy and a 0.95 F1 score, compared with 0.80 and 0.84 for the averaged-score baseline. SHAP explanations inform recommendations, and revised pages gained an average of 1.4 points on a 10-point quality scale.

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