Temporal Cluster graphs for visualizing Trends

Organizations and firms are capturing increasingly more data about their customers, suppliers,competitors and business environment. Most of this data is multidimensional and temporal innature. Data mining and business intelligence technique are often used to discover in suchdata. We propose a new data analysis and visualization technique for representing trends andtemporal data using K-means clustering based approach. And we introduce a system thatimplements the temporal clustered graph construct which maps temporal data to a twodimensional directed graph that identifies trends in dominant data types over time. In thispaper, we present our temporal clustered based technique and its implementation andperformance.References