Research on Intelligent Campus and Visual Teaching System Based on Internet of Things
Tao Xu,
Zhi-hong Wang,
Xian-qi Zhang and
Xuefeng Shao
Mathematical Problems in Engineering, 2022, vol. 2022, 1-10
Abstract:
The rapid development of Internet of things technology provides robust conditions for building a perfect intelligent campus. A visual teaching question answering system is essential for creating a smart campus, significantly improving education quality. However, the accuracy of the existing teaching question answering system is not high. To solve this problem, this paper proposes a visual teaching system based on a knowledge map. The system mainly includes two parts: problem processing and answer search. In the part of problem processing, combined with the pretraining language model, a new model framework is constructed to deal with the problem of entity reference recognition, entity link, and relationship extraction. By setting three kinds of classification labels, the problem is divided into simple, chain, and multientity problems. Different solutions are given to the above three classification problems in the answer search part. The experimental results show that the answer accuracy of this system is higher than other comparison methods.
Date: 2022
References: Add references at CitEc
Citations:
Downloads: (external link)
http://downloads.hindawi.com/journals/mpe/2022/4845978.pdf (application/pdf)
http://downloads.hindawi.com/journals/mpe/2022/4845978.xml (application/xml)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:4845978
DOI: 10.1155/2022/4845978
Access Statistics for this article
More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().