Intelligent Music Website built using PHP&MySQL
Oral Defence Date:
Prof. James Wong & Assistant Prof. Hao Yue
The amount of song in the world is increasing quickly. There are lots of new songs coming out each year. As the result, the research for intelligent music system has become popular in the industry, as well as in the academic. In this project, we built an intelligent music website, FiSong, using PHP/MySQL. The idea of FiSong came after our investigation of the existing music websites. In general music websites, the user can find the song they want by its title. Also, the websites would provide the user some recommendation songs. However, as the demand and technology keep growing in the industry, these features are not enough. We need to develop a more intelligent music website that satisfies people’s need today. FiSong has a song matching feature which implements by using Knuth Morris Pratt algorithm and Longest Common Subsequence algorithm. It can find the best song based on user’s input in linear time. Also, FiSong uses cluster analysis for song recommendation system which allows it to provide recommendations in linear time. There is no music website that has such features in the world right now.
intelligent website, song recommendation, lyric matching