Descriptions from the Customers

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.