This study discovers a certain complementary relationship between different algorithms after conducting a comprehensive and in-depth analysis of proposal algorithms. This study proposes a big data music individualization proposal method based on big data analysis, which integrates user behaviour, behaviour context, user information, and music work information, based on traditional music proposal methods; improves the collaborative filtering proposal algorithm based on user behaviour; and calculates the semantic similarity between lyrics, as well as the song co-occurrence similarity based on the user’s music download history. Because the lyrics represent the thoughts and feelings that the song wishes to convey to the listeners, the proposal module is completed, and the music proposal system is realized, by combining the two different similar information, using the improved algorithm and the Hadoop distributed framework. The music similarity and label similarity are combined to alleviate the problem of cold start and data sparseness, and a mixed similarity calculation formula is proposed to calculate the similarity between music. The accuracy similarity of the big data music proposal model proposed in this study is improved by about 20% through experimental comparison when compared with the collaborative filtering model and the hybrid model. It reflects the efficiency, scalability, and stability of the music proposal system as well as the ability to meet users’ individual music needs.

The article discusses the pedagogical potential of Ukrainian song folklore in the context of current trends in modern musical pedagogy. Song folklore is considered as the main identifier of the national musical tradition and reflects the non-musical factors of its specificity. These factors ensure the success of the study of Ukrainian music by representatives of other cultures and reflect the main ideas of the cross-cultural direction of music education, in the mainstream of which the interactions of the modern pedagogical experience of Ukraine and China are formed. Ukrainian song folklore as a semiotic system is considered as didactic material, which is aimed at the formation of the semiotic competence of a music teacher. The proposed method allows the student to form a conscious perception of a folk song as a "genocode" of national culture, which is expressed in the symbolic form of the musical language. Song folklore is also promising for the integrational direction of artistic pedagogy. It is based on the principle of using interdisciplinary connections of various types of arts in the educational process.