基于传感器和信息检索技术的个性化音乐教学服务推荐

Q4 Engineering Measurement Sensors Pub Date : 2024-05-06 DOI:10.1016/j.measen.2024.101207
Hui Lu
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引用次数: 0

摘要

为了充分利用现有的音乐信息资源,人们发现音乐信息检索技术对于个性化音乐教学具有重要的研究意义。总体而言,音乐信息检索技术仍处于实验探索阶段,缺乏技术实用体系。在此背景下,本文提出了可根据用户偏好有效调整信息服务内容的推荐算法。然而,推荐算法仍处于不成熟和复杂的阶段,其准确性仍存在问题。针对推荐准确性的问题,本文利用信息检索技术来优化推荐算法。将这两种算法结合起来进行推荐。推荐算法中影响推荐结果的主要步骤包括相似度计算、近邻选择法、分数预测法计算等。实验结果表明,所提出的算法能有效解决用户存在的问题,还能准确检索出用户感兴趣的内容,大大提高了推荐内容的多样性。我们利用算法学习创建个性化的音乐教学系统,使学生能够自主地朝着自我发展的目标前进,最终实现促进学生个性和谐发展的目标。
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Personalized music teaching service recommendation based on sensor and information retrieval technology

In order to fully utilize the existing resources of music information, people have found that music information retrieval technology has important research significance for personalized music teaching. Overall, music information retrieval technology is still in the experimental exploration stage and lacks technical and practical systems. In this context, this article proposes recommendation algorithms that can effectively adjust the content of information services based on user preferences. However, recommendation algorithms are still in an immature and complex stage, and there are still issues with their accuracy. In response to the issue of recommendation accuracy, this article utilizes information retrieval technology to optimize recommendation algorithms. Combine these two algorithms for recommendation. The main steps that affect recommendation results in recommendation algorithms include similarity calculation, nearest neighbor selection method, and score prediction method calculation. The experimental results indicate that the proposed algorithm can effectively solve the existing problems of users, and can also accurately retrieve the content of interest, greatly improving the diversity of the proposed content. We use utilizing algorithmic learning to create a personalized music teaching system that enables students to independently advance towards their self-development goals, ultimately achieving the goal of promoting the harmonious development of students' personalities.

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来源期刊
Measurement Sensors
Measurement Sensors Engineering-Industrial and Manufacturing Engineering
CiteScore
3.10
自引率
0.00%
发文量
184
审稿时长
56 days
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