%0 Journal Article %A GAO Weijun %A ZHU Jing %A ZHAO Huayang %A LI Lei %T Personalized Product Review Summary Generation Based on TRF-IM Model %D 2023 %R 10.3778/j.issn.1002-8331.2107-0144 %J Computer Engineering and Applications %P 135-142 %V 59 %N 2 %X Aiming at the problems of insufficient contextual understanding of reviews, insufficient parallelism and long-distance text dependence in the process of generating a summary of the traditional model of hotel review summary generation, a personalized hotel review summary generation method based on TRF-IM(improved mask for transformer) model is proposed. This method uses the Transformer decoder structure to model the review summary task. By improving the masking method in the structure, the source review content can better learn the contextual semantic information. At the same time, user-type personalized word feature information is introduced to generate high-quality personalized hotel review summaries that meet user needs. The experimental results show that the proposed model achieves higher scores on the ROUGE indicator than the traditional model, and generates high-quality personalized hotel review summaries. %U http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.2107-0144