Research on Music Programming and Composition Optimization Methods Based on Big Data Technology: A Case Study of Musical Culture Analysis in Mediterranean Archaeological Sites

Abstract

This study aims to explore music programming and composition optimization methods based on big data technology, incorporating an analysis of musical culture from Mediterranean archaeological sites to provide new perspectives for archaeology and cultural heritage research. With the continuous advancement of big data technology, the music industry has begun to utilize data analysis, machine learning, and other technologies to enhance the efficiency and quality of music creation. Firstly, this paper reviews the challenges of traditional music programming and composition methods, including subjectivity and creative limitations. Secondly, by analyzing large-scale music datasets and integrating machine learning algorithms, a music programming and composition optimization method based on big data technology is proposed. This method employs data mining techniques to extract patterns and rules from music data, assisting music creators in decision-making, thereby improving the efficiency and quality of their works. Finally, the effectiveness of the proposed method is verified through experiments, and its application prospects in actual music creation are discussed. This research is of great significance for promoting technological innovation and development in the field of music creation, while also providing new methodological support for the study of musical culture in Mediterranean archaeological sites.