Product descriptions play an important role in the e-commerce ecosystem. Yet, on leading e-commerce websites product descriptions are often lacking or missing. In this work, we suggest to overcome these issues by generating product descriptions from user reviews. We identify the set of candidates using a supervised approach that extracts review sentences in their original form, diversifies them, and selects the top candidates. We present extensive analyses of the generated descriptions, including a comparison to the original descriptions and examination of review coverage. We also perform an A/B test that demonstrates the impact of presenting our descriptions on user traffic.

中文翻译：

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来自客户的描述

产品描述在电子商务生态系统中发挥着重要作用。然而，在领先的电子商务网站上，产品描述往往缺乏或缺失。在这项工作中，我们建议通过从用户评论中生成产品描述来克服这些问题。我们使用监督方法识别候选集，该方法提取原始形式的评论句子，使其多样化，并选择最佳候选者。我们对生成的描述进行了广泛的分析，包括与原始描述的比较和审查范围的检查。我们还进行了 A/B 测试，展示了呈现我们的描述对用户流量的影响。