@article{Li_Li_Zong_2019, title={Towards Personalized Review Summarization via User-Aware Sequence Network}, volume={33}, url={https://ojs.aaai.org/index.php/AAAI/article/view/4640}, DOI={10.1609/aaai.v33i01.33016690}, abstractNote={<p>We address personalized review summarization, which generates a condensed summary for a user’s review, accounting for his preference on different aspects or his writing style. We propose a novel personalized review summarization model named User-aware Sequence Network (USN) to consider the aforementioned users’ characteristics when generating summaries, which contains a user-aware encoder and a useraware decoder. Specifically, the user-aware encoder adopts a user-based selective mechanism to select the important information of a review, and the user-aware decoder incorporates user characteristic and user-specific word-using habits into word prediction process to generate personalized summaries. To validate our model, we collected a new dataset <em>Trip</em>, comprising 536,255 reviews from 19,400 users. With quantitative and human evaluation, we show that USN achieves state-ofthe-art performance on personalized review summarization.</p>}, number={01}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Li, Junjie and Li, Haoran and Zong, Chengqing}, year={2019}, month={Jul.}, pages={6690-6697} }