Application of Collaborative Filtering and Data Mining Technology in Personalized National Music Recommendation and Teaching

Personalized music recommendations can accurately push the music of interest from a massive song library based on user information when the user’s listening needs are blurred. To this end, this paper proposes a method of national music recommendation based on ontology modeling and context awareness...

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Autores principales:	Meilin Lu, Fangfang Deng
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi-Wiley 2021
Materias:	Technology (General) T1-995 Science (General) Q1-390
Acceso en línea:	https://doaj.org/article/1a57579012434441a3a27c8228baf6d5
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spelling	oai:doaj.org-article:1a57579012434441a3a27c8228baf6d52021-11-15T01:19:24ZApplication of Collaborative Filtering and Data Mining Technology in Personalized National Music Recommendation and Teaching1939-012210.1155/2021/3140341https://doaj.org/article/1a57579012434441a3a27c8228baf6d52021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/3140341https://doaj.org/toc/1939-0122Personalized music recommendations can accurately push the music of interest from a massive song library based on user information when the user’s listening needs are blurred. To this end, this paper proposes a method of national music recommendation based on ontology modeling and context awareness to explore the use of music resources to portray user preferences better. First, the expectation-maximization algorithm is used to cluster users and ethnic music scores, and similar users and music are divided into clusters. The similarity of objects in the same cluster is higher, and the similarity of objects in different clusters is lower. Second, we designed a multilayer collaborative filtering ethnic music recommendation model based on ontology modeling and tensor decomposition. This model uses ontology to construct a user knowledge model and integrates similarity measures in multiple situations. The actual case test and user feedback analysis show that the designed personalized national music model has good application and promotion effects.Meilin LuFangfang DengHindawi-WileyarticleTechnology (General)T1-995Science (General)Q1-390ENSecurity and Communication Networks, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Technology (General) T1-995 Science (General) Q1-390
spellingShingle	Technology (General) T1-995 Science (General) Q1-390 Meilin Lu Fangfang Deng Application of Collaborative Filtering and Data Mining Technology in Personalized National Music Recommendation and Teaching
description	Personalized music recommendations can accurately push the music of interest from a massive song library based on user information when the user’s listening needs are blurred. To this end, this paper proposes a method of national music recommendation based on ontology modeling and context awareness to explore the use of music resources to portray user preferences better. First, the expectation-maximization algorithm is used to cluster users and ethnic music scores, and similar users and music are divided into clusters. The similarity of objects in the same cluster is higher, and the similarity of objects in different clusters is lower. Second, we designed a multilayer collaborative filtering ethnic music recommendation model based on ontology modeling and tensor decomposition. This model uses ontology to construct a user knowledge model and integrates similarity measures in multiple situations. The actual case test and user feedback analysis show that the designed personalized national music model has good application and promotion effects.
format	article
author	Meilin Lu Fangfang Deng
author_facet	Meilin Lu Fangfang Deng
author_sort	Meilin Lu
title	Application of Collaborative Filtering and Data Mining Technology in Personalized National Music Recommendation and Teaching
title_short	Application of Collaborative Filtering and Data Mining Technology in Personalized National Music Recommendation and Teaching
title_full	Application of Collaborative Filtering and Data Mining Technology in Personalized National Music Recommendation and Teaching
title_fullStr	Application of Collaborative Filtering and Data Mining Technology in Personalized National Music Recommendation and Teaching
title_full_unstemmed	Application of Collaborative Filtering and Data Mining Technology in Personalized National Music Recommendation and Teaching
title_sort	application of collaborative filtering and data mining technology in personalized national music recommendation and teaching
publisher	Hindawi-Wiley
publishDate	2021
url	https://doaj.org/article/1a57579012434441a3a27c8228baf6d5
work_keys_str_mv	AT meilinlu applicationofcollaborativefilteringanddataminingtechnologyinpersonalizednationalmusicrecommendationandteaching AT fangfangdeng applicationofcollaborativefilteringanddataminingtechnologyinpersonalizednationalmusicrecommendationandteaching
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Application of Collaborative Filtering and Data Mining Technology in Personalized National Music Recommendation and Teaching

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