Multi Cultural Music Remote Assistant Teaching System Based on Mobile Internet of Things

Ren, Yang-lu; Jun, Zhou; Wu, Yangbo

doi:10.1007/978-3-030-94551-0_44

Cited by 1 publication

(1 citation statement)

References 12 publications

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“…This is in response to the fact that these students share more coursework than other students. By mining the learner's browsing history, a number of researchers have developed a hybrid recommendation technique that is based on the AprioriAlI algorithm as well as the learner's behavior and preferences [25,26,27].…”

Section: Related Workmentioning

confidence: 99%

Recommendation method of teaching resources for professional music courses based on knowledge graph

xin

2023

Preprint

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There is an abundance of materials for use in professional music courses, but it can be difficult for consumers to quickly and efficiently obtain the specific knowledge they require. Additionally, there is a general lack of data collected on online learning, which renders the recommendation effect of music course resources insufficient. In this study, we use technologies connected to the knowledge graph to the field of online education in order to create a system capable of recommending acceptable educational materials for use in professional music classes. In order to construct a recommendation model using multi-task feature learning, knowledge graphs are embedded within tasks, and high-order connections between latent features and entities are constructed across tasks using cross-compression units. It is possible to achieve success by recommending relevant course materials for individual students based on their requirements, interests, and present skill levels. In terms of its ability to generate suggestions, the proposed knowledge spectrogram-based teaching resource recommendation system for professional music courses outperforms four baseline models on a number of publicly available datasets. This method has some practical utility in the domain of course resource suggestion, and its training time is less than that of the comparison model.

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Section: Related Workmentioning

confidence: 99%

Recommendation method of teaching resources for professional music courses based on knowledge graph

xin

2023

Preprint

View full text Add to dashboard Cite

show abstract

Multi Cultural Music Remote Assistant Teaching System Based on Mobile Internet of Things

Cited by 1 publication

References 12 publications

Recommendation method of teaching resources for professional music courses based on knowledge graph

Recommendation method of teaching resources for professional music courses based on knowledge graph

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