Efficient Memory Saving Scheme of Multi－Feature Indexing for Music Databases

The management of large collections of music data in a multimedia database has received much attention in the past few years. In the most of current works, the researchers extract the features, such as melodies, rhythms and chords, from the music data and develop indices that will help to retrieve the relevant music quickly and accurately. Several reports have pointed out that these features of music can be transformed and represented in the forms of music feature strings or numeric values such that the indices can be created for music retrievals. However, there is only a small number of existing approaches introduced multi-feature index structures for music queries while most of researches are for developing single feature indices. The existing music multi-feature index structures are memory consuming and lack of scalability. In this paper, we will propose a hybrid index structure which can save lots of memory for music multi-feature indexing. Our experimental results also show that the new approach outperforms existing multi-feature index scheme for memory needed.