Construction method of knowledge graph under machine learning
by Peifu Han; Junjun Guo; Hua Lai; Qianli Song
International Journal of Grid and Utility Computing (IJGUC), Vol. 13, No. 1, 2022

Abstract: With the increasing trade among China and Southeast Asian countries, cultural exchanges have become more and more intensified. Convenient language communication constitutes an important part of the cooperation channels among different countries. To explore the named entity recognition (NER) in the field of knowledge graph construction, the Vietnamese grammar and word formation are analysed deeply in this study, aiming to solve the low recognition precision and low network calculation efficiency in Vietnamese named entity recognition. Firstly, the Vietnamese person names, location names, and institution names in Vietnamese corpus are collected statistically to build a corresponding entity database to assist the Vietnamese named entity recognition. Then, a Vietnamese named entity recognition model is proposed based on residual dense block (RDB) convolutional neural network (CNN).

Online publication date: Fri, 11-Mar-2022

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Grid and Utility Computing (IJGUC):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com