Title :
Trend cluster analysis using self organizing maps
Author :
Amin, Mohd Nasir Mat ; Nohuddin, Puteri N. E. ; Zainol, Zuraini
Author_Institution :
Dept. of Comput. Sci., Nat. Defense Univ. of Malaysia, Kuala Lumpur, Malaysia
Abstract :
Trend cluster analysis using Self Organization Maps (SOM) is an application for clustering time series data. The application is able to cluster and display the time series data into trend lines graphs, and also identify trend variations in time series data. The system can process a large number of records as well as a smaller datasets. The results generated by the application are useful for analyzing large data which is often hard to analyze using normal spreadsheet software. The system has been developed using Matlab SOM functions and adopted SOM learning technique to cluster time series data. Based on the experiments, the test results have shown that the application is able to accommodate large sets of data and produce the trend lines graphs.
Keywords :
learning (artificial intelligence); pattern clustering; self-organising feature maps; spreadsheet programs; time series; Matlab SOM function; SOM learning technique; normal spreadsheet software; self organizing maps; time series data clustering; time series data trend variations; trend cluster analysis; trend line graph; Data mining; Forecasting; Market research; Organizations; Prototypes; Stock markets; Time series analysis; SOM; cluster analysis; clustering; time series; trend line;
Conference_Titel :
Information and Communication Technologies (WICT), 2014 Fourth World Congress on
Print_ISBN :
978-1-4799-8114-4
DOI :
10.1109/WICT.2014.7077306
