Music Recommendation Engine
- Soni Kumari
- B. I. Khodhanpur
Component, filtering, uploading, styling, insert
A Recommender system for music data is proposed here, which assists customers in searching music data and provides results with items using his own preference. This system first extracts unique properties of music like Genre, Artist, Album, Language, Length and Year from the music file. This extracted data is stored on the database. Each stored property is analyzed using item based Collaborating filtering algorithm and cosine similarity method. After acquiring records, the system recommends items appropriate to user’s own choice. The main objective of this paper is to design a recommender that exploits advantages of item based Collaborating filtering for high quality of recommendation. This approach is one of the most powerful search techniques for finding an optimized solution of matching songs to be recommended to the user.
Volume 2 Issue 2
Pages. 2680-2683
