Exploring the Chemical Space of Multitarget Ligands Using Aligned Self-Organizing Maps

Aligned Self-Organizing Maps

− The concept of similarity is important for many data mining related applications such as content-based music retrieval. Defining similarity can be very difficult if several aspects are involved. For example, music similarity depends on the melody, rhythm, or instruments. The Self-Organizing Map is a powerful tool to visualize how the data looks like from a certain perspective of similarity. I...

using game theory techniques in self-organizing maps training

شبکه خود سازمانده پرکاربردترین شبکه عصبی برای انجام خوشه بندی و کوانتیزه نمودن برداری است. از زمان معرفی این شبکه تاکنون، از این روش در مسائل مختلف در حوزه های گوناگون استفاده و توسعه ها و بهبودهای متعددی برای آن ارائه شده است. شبکه خودسازمانده از تعدادی سلول برای تخمین تابع توزیع الگوهای ورودی در فضای چندبعدی استفاده می کند. احتمال وجود سلول مرده مشکلی اساسی در الگوریتم شبکه خودسازمانده به حسا...

Exploring Forensic Data with Self-Organizing Maps

Green Product Consumers Segmentation Using Self-Organizing Maps in Iran

This study aims to segment the market based on demographical, psychological, and behavioral variables, and seeks to investigate their relationship with green consumer behavior. In this research, self-organizing maps are used to segment and to determine the features of green consumer behavior. This was a survey type of research study in which eight variables were selected from the demographical,...

Space-in-Time and Time-in-Space Self-Organizing Maps for Exploring Spatiotemporal Patterns

Spatiotemporal data pose serious challenges to analysts in geographic and other domains. Owing to the complexity of the geospatial and temporal components, this kind of data cannot be analyzed by fully automatic methods but require the involvement of the human analyst’s expertise. For a comprehensive analysis, the data need to be considered from two complementary perspectives: (1) as spatial di...