Proceedings of the 2nd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2023)

A Study of Music Teaching Techniques Based on Deep Learning

Authors
Jihong Duan1, *
1Xiangnan University, Chenzhou, China
*Corresponding author. Email: 444892870@qq.com
Corresponding Author
Jihong Duan
Available Online 10 August 2023.
DOI
10.2991/978-94-6463-198-2_114How to use a DOI?
Keywords
deep learning; big data research; support under big data; music teaching; deep teaching
Abstract

In this paper, we simulate the human discovery behaviour of topic web pages in the crawling strategy, combine the topic discrimination model, the breadth traversal crawling strategy and the depth traversal crawling strategy to implement an improved topic URL crawling strategy that allows crawlers to crawl topic-related URLs in priority to improve web crawling efficiency. The experiment used Sina military news as the crawler's data object, and "Russia-Ukraine conflict" news as the crawler's topic, and analysed the crawler's running time and the proportion of topic pages by comparing with the breadth-first strategy, depth-first strategy, PageRank strategy and best-first search strategy. The experimental results show that the improved theme URL crawler strategy, which improves the calculation of the similarity of web page themes, helps the crawler to obtain URLs with better themes and improves the efficiency of the crawler, which is important for solving the problem of accessing open source web information. This paper examines the application and in-depth development of deep learning techniques for teaching music, combining computers and music teaching in an in-depth study that adds seeming models and approaches to teaching.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2nd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2023)
Series
Atlantis Highlights in Computer Sciences
Publication Date
10 August 2023
ISBN
10.2991/978-94-6463-198-2_114
ISSN
2589-4900
DOI
10.2991/978-94-6463-198-2_114How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Jihong Duan
PY  - 2023
DA  - 2023/08/10
TI  - A Study of Music Teaching Techniques Based on Deep Learning
BT  - Proceedings of the 2nd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2023)
PB  - Atlantis Press
SP  - 1111
EP  - 1116
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-198-2_114
DO  - 10.2991/978-94-6463-198-2_114
ID  - Duan2023
ER  -