Applied and Computational Engineering

- The Open Access Proceedings Series for Conferences


Proceedings of the 3rd International Conference on Signal Processing and Machine Learning

Series Vol. 4 , 30 May 2023


Open Access | Article

Visualization of data analysis platform — Taking QQ music recommendation system as an example

Xinyue Li * 1
1 The High School Affiliated to Renmin University of China, Beijing, China, 100089

* Author to whom correspondence should be addressed.

Applied and Computational Engineering, Vol. 4, 63-69
Published 30 May 2023. © 30 May 2023 The Author(s). Published by EWA Publishing
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Citation Xinyue Li. Visualization of data analysis platform — Taking QQ music recommendation system as an example. ACE (2023) Vol. 4: 63-69. DOI: 10.54254/2755-2721/4/20230351.

Abstract

With the rapid development of big data technology, people's demand for personalized music recommendation systems is growing more and more urgent. However, the current music recommendation system still has some problems, such as inaccurate recommendations and too slow recommendation speeds, as well as cold starts and data sparsity caused by massive data. In order to design and implement a music recommendation system for the recommendation system storage caused by the continuous increase of data, insufficient storage, and computing power, this paper improved the QQ music recommendation system based on the collaborative filtering recommendation algorithm of the offline data warehouse technology project. After testing, the music recommendation system designed in this paper has good stability, scalability, and efficiency.

Keywords

Data Warehouse, Text Similarity, Big Data, Recommendation

References

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Data Availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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Volume Title
Proceedings of the 3rd International Conference on Signal Processing and Machine Learning
ISBN (Print)
978-1-915371-55-3
ISBN (Online)
978-1-915371-56-0
Published Date
30 May 2023
Series
Applied and Computational Engineering
ISSN (Print)
2755-2721
ISSN (Online)
2755-273X
DOI
10.54254/2755-2721/4/20230351
Copyright
30 May 2023
Open Access
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Copyright © 2023 EWA Publishing. Unless Otherwise Stated