2019/01/14 by Xuehui Sun, Sun, Xuehui, Zihan Zhou +3
Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Multimodal Machine Learning Applications #Sentiment Analysis and Opinion Mining #Topic Modeling #cs.AI #cs.CL #cs.CV
paper · pdf · doi:10.48550/arxiv.1901.04140
5 pages
arxiv created 2019/01/14 · openalex publication_date 2019/01/14 · arxiv updated 2019/01/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In the current field of computer vision, automatically generating texts from given images has been a fully worked technique. Up till now, most works of this area focus on image content describing, namely image-captioning. However, rare researches focus on generating product review texts, which is ubiquitous in the online shopping malls and is crucial for online shopping selection and evaluation. Different from content describing, review texts include more subjective information of customers, which may bring difference to the results. Therefore, we aimed at a new field concerning generating review text from customers based on images together with the ratings of online shopping products, which appear as non-image attributes. We made several adjustments to the existing image-captioning model to fit our task, in which we should also take non-image features into consideration. We also did experiments based on our model and get effective primary results.