Validating the stable clustering of songs in a structured 3D SOM

• Main Authors: Azcarraga, Arnulfo P., Caronongan, Arturo, Setiono, Rudy, Manalili, Sean
• Format: text
• Published: Animo Repository 2016
• Subjects: Self-organizing maps; Software Engineering
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/1199; https://animorepository.dlsu.edu.ph/context/faculty_research/article/2198/type/native/viewcontent
• Institution: De La Salle University

A structured 3D SOM is an extension of a Self-Organizing Map from 2D to 3D in such a way that a pre-defined structure is built into the design of the 3D map. The structured 3D SOM is a 3×3×3 structure that has a distinct core cube in the center and exterior cubes around the core. The current application of the structured SOM, as a digital music archive, only uses the 8 corner cubes among the 26 exterior cubes. Given that the SOM has a built-in structure, the SOM learning algorithm is modified to include a four-phase learning and labeling phase. The first phase is meant to position the music files in their general locations within the core cube. The second phase positions the music files in their respective corner cubes according to their music genre. The second phase is therefore a semi-supervised version of the SOM algorithm which leads to the stability of the trained SOM in terms of the general distribution of the music files in the core cube. The third phase does a fine adjustment of the weight vectors in the core cube and finalizes the training of the 3D SOM. The final fourth phase is the labeling of the core cube and the association (uploading) of music files to specific nodes in the core cube. Based on the pre-defined structure of the 3D SOM, a precise measure is developed to measure the quality of the resulting trained SOM (in this case, the music archive), as well as the quality of the different categories/genres of music albums based on a novel measure of the distortion values of music files with respect to their respective music genres. © 2016 IEEE.