Journal of Guangxi Normal University(Natural Science Edition) ›› 2022, Vol. 40 ›› Issue (3): 31-39.doi: 10.16088/j.issn.1001-6600.2021091504

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Construction of Chinese Multimodal Knowledge Base

CHAO Rui, ZHANG Kunli*, WANG Jiajia, HU Bin, ZHANG Weicong, HAN Yingjie, ZAN Hongying   

  1. School of Computer and Artificial Intelligence, Zhengzhou University, Zhengzhou Henan 450001, China
  • Received:2021-09-15 Revised:2021-12-28 Online:2022-05-25 Published:2022-05-27

Abstract: Multi-modal fusion aims to integrate multiple modal information to obtain a consistent and common model output, which is a basic problem in the multi-modal field. Through the fusion of multimodal information, more comprehensive features can be obtained and the robustness of the model can be improved. At present, multimodal fusion technology has become one of the core research topics in the field of multimodality. Based on Imagenet, HowNet and CCD, this paper constructs a new multimodal knowledge base through manual annotation. The calibration has completed the mapping of 21 455 noun concepts in ImageNet, effectively mapping the concepts in HowNet and CCD to ImageNet. The data set can be applied to natural language processing tasks and computer vision tasks, and improve the task effect through picture information and concept information. In image classification, by adding HowNet and ImageNet concepts, more image features can be integrated to assist classification. In semantic understanding, image information can be better understood by adding image information through mapping.

Key words: multimodal infomation, multimodal fusion, ImageNet, HowNet, CCD

CLC Number: 

  • TP391.1
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