<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In order to solve the problem of information overload of music system under large data background, this paper studies the design scheme of distributed music recommendation system based on Hadoop. The proposed algorithm is based on the MapReduce distributed computing framework, which has high scalability and performance, and can be applied to the calculation and analysis of off-line data efficiently. The music recommendation system designed in this paper also includes client, server interface, database and ETL operation, which can calculate a set of complete recommendation system from user operation end to server and data calculation. In order to improve the accuracy of the recommendation algorithm, this paper introduces k-means clustering algorithm to improve the recommendation algorithm based on user-based collaborative filtering.The experimental results show that the accuracy of the proposed algorithm has been significantly improved after the introduction of k-means.</p>
</abstract>

In order to solve the problem of information overload of music system under large data background, this paper studies the design scheme of distributed music recommendation system based on Hadoop. The proposed algorithm is based on the MapReduce distributed computing framework, which has high scalability and performance, and can be applied to the calculation and analysis of off-line data efficiently. The music recommendation system designed in this paper also includes client, server interface, database and ETL operation, which can calculate a set of complete recommendation system from user operation end to server and data calculation. In order to improve the accuracy of the recommendation algorithm, this paper introduces k-means clustering algorithm to improve the recommendation algorithm based on user-based collaborative filtering.The experimental results show that the accuracy of the proposed algorithm has been significantly improved after the introduction of k-means.

Design and Implementation of Music Recommendation System Based on Hadoop

International Journal of Advanced Network, Monitoring and Controls

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Design and Implementation of Music Recommendation System Based on Hadoop"}

In order to solve the problem of information overload of music system under large data background, this paper studies the design scheme of distributed music...

Design and Implementation of Music Recommendation System Based on Hadoop

Online veröffentlicht: 07. Mai 2018

Seitenbereich: 126 - 132

DOI: https://doi.org/10.21307/ijanmc-2018-045

Schlüsselwörter
Music Recommendation, K-means Clustering, Collaborative Filtering, Recommendation Algorithm, Hadoop

© 2018 Zhao Yufeng et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Design and Implementation of Music Recommendation System Based on Hadoop

Online veröffentlicht: 07. Mai 2018

Seitenbereich: 126 - 132

DOI: https://doi.org/10.21307/ijanmc-2018-045

SchlüsselwörterMusic Recommendation, K-means Clustering, Collaborative Filtering, Recommendation Algorithm, Hadoop

© 2018 Zhao Yufeng et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Figure 5.

Figure 6.

Figure 7.

Figure 8.

Schlüsselwörter
Music Recommendation, K-means Clustering, Collaborative Filtering, Recommendation Algorithm, Hadoop