摘要：Dialogue sentiment analysis is a hot topic in the field of artificial intelligence in recent years, in which the construction of multimodal corpus is the key part of dialogue sentiment analysis. With the rapid development of the Internet of Things (IoT), it provides a new means to collect the multiparty dialogues to construct a multimodal corpus. The rapid development of Mobile Edge Computing (MEC) provides a new platform for the construction of multimodal corpus. In this paper, we construct a multimodal corpus on MEC servers to make full use of the storage space distributed at the edge of the network according to the procedure of constructing a multimodal corpus that we propose. At the same time, we build a deep learning model (sentiment analysis model) and use the constructed corpus to train the deep learning model for sentiment on MEC servers to make full use of the computing power distributed at the edge of the network. We carry out experiments based on real-world dataset collected by IoT devices, and the results validate the effectiveness of our sentiment analysis model.

ISSN号：1687-5265

卷、期、页：卷: 2022

发表日期：2022-08-05

影响因子：3.632900

期刊分区（SCI为中科院分区）：三区

收录情况：SCIE（科学引文索引网络版）,EI（工程索引）

发表期刊名称：COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE

参与作者：梁处,许嘉杰,赵杰,陈莹

第一作者：黄霁崴

论文类型：期刊论文

论文概要：梁处,许嘉杰,赵杰,陈莹,黄霁崴，Deep Learning-Based Construction and Processing of Multimodal Corpus for IoT Devices in Mobile Edge Computing，COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE，2022，卷: 2022

论文题目：Deep Learning-Based Construction and Processing of Multimodal Corpus for IoT Devices in Mobile Edge Computing