Knowledge Commons of Institute of Automation,CAS
Multi-Interactive Memory Network for Aspect Based Multimodal Sentiment Analysis | |
Xu, Nan1,2; Mao, Wenji1,2; Chen, Guandan1,2 | |
2019-01 | |
会议名称 | The Thirty-Third AAAI Conference on Artificial Intelligence |
会议日期 | January 27 – February 1, 2019 |
会议地点 | Honolulu, Hawaii, USA |
摘要 | As a fundamental task of sentiment analysis, aspect-level sentiment analysis aims to identify the sentiment polarity of a specific aspect in the context. Previous work on aspect-level sentiment analysis is text-based. With the prevalence of multimodal user-generated content (e.g. text and image) on the Internet, multimodal sentiment analysis has attracted increasing research attention in recent years. In the context of aspect-level sentiment analysis, multimodal data are often more important than text-only data, and have various correlations including impacts that aspect brings to text and image as well as the interactions associated with text and image. However, there has not been any related work carried out so far at the intersection of aspect-level and multimodal sentiment analysis. To fill this gap, we are among the first to put forward the new task, aspect based multimodal sentiment analysis, and propose a novel Multi-Interactive Memory Network (MIMN) model for this task. Our model includes two interactive memory networks to supervise the textual and visual information with the given aspect, and learns not only the interactive influences between cross-modality data but also the self influences in single-modality data. We provide a new publicly available multimodal aspect-level sentiment dataset to evaluate our model, and the experimental results demonstrate the effectiveness of our proposed model for this new task. |
收录类别 | EI |
资助项目 | Chinese Academy of Science Grant[ZDRW-XH-2017-3] ; Ministry of Science and Technology (China)[2016QY02D0305] ; National Natural Science Foundation of China (NSFC)[71621002] ; National Natural Science Foundation of China[11832001] ; National Natural Science Foundation of China[61671450] ; National Natural Science Foundation of China[61671450] ; National Natural Science Foundation of China[11832001] ; National Natural Science Foundation of China (NSFC)[71621002] ; Ministry of Science and Technology (China)[2016QY02D0305] ; Chinese Academy of Science Grant[ZDRW-XH-2017-3] |
语种 | 英语 |
七大方向——子方向分类 | 多模态智能 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/39141 |
专题 | 多模态人工智能系统全国重点实验室_互联网大数据与信息安全 |
通讯作者 | Xu, Nan |
作者单位 | 1.Institute of Automation, Chinese Academy of Sciences 2.University of Chinese Academy of Sciences |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Xu, Nan,Mao, Wenji,Chen, Guandan. Multi-Interactive Memory Network for Aspect Based Multimodal Sentiment Analysis[C],2019. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Multi-Interactive Me(371KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论