Conclusion
Experimental results show that the CrowdDesigner outperforms several strong personalized product description generation methods in personal interest coverage, language organization and detailed product information. In addition, the personalized product descriptions generated from the Crowd-Designer can be used as product recommendation texts on the E-commerce web pages, product recommendation pages in mobile apps, offline electronic advertising screens and so on.
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Acknowledgements
This work was partially supported by the National Key RD Program of China (2019QY0600), the National Science Fund for Distinguished Young Scholars (62025205), the National Natural Science Foundation of China (Grant Nos. 62032020, 61960206008, 62102317, 62002292), and the Natural Science Basic Research Plan in Shaanxi Province of China (2020JQ-207).
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Zhang, Q., Guo, B., Liu, S. et al. CrowdDesigner: information-rich and personalized product description generation. Front. Comput. Sci. 16, 166339 (2022). https://doi.org/10.1007/s11704-022-1193-7
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DOI: https://doi.org/10.1007/s11704-022-1193-7