Generating E-commerce product titles and predicting their quality

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Abstract

E-commerce platforms present products using titles that summarize product information. These titles cannot be created by hand, therefore an algorithmic solution is required. The task of automatically generating these titles given noisy user provided titles is one way to achieve the goal. The setting requires the generation process to be fast and the generated title to be both human-readable and concise. Furthermore, we need to understand if such generated titles are usable. As such, we propose approaches that (i) automatically generate product titles, (ii) predict their quality. Our approach scales to millions of products and both automatic and human evaluations performed on real-world data indicate our approaches are effective and applicable to existing e-commerce scenarios.

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APA

de Souza, J. G. C., Kozielski, M., Mathur, P., Chang, E., Guerini, M., Negri, M., … Matusov, E. (2018). Generating E-commerce product titles and predicting their quality. In INLG 2018 - 11th International Natural Language Generation Conference, Proceedings of the Conference (pp. 233–243). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w18-6530

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