Vertical Data Mining on Very Large Data Sets
William Perrizo (North Dakota State University, USA), Qiang Ding (Chinatelecom Americas, USA), Qin Ding (East Carolina University, USA) and Taufik Abidin (North Dakota State University, USA)
Copyright: © 2009
Due to the rapid growth of the volume of data that are available, it is of importance and challenge to develop scalable methodologies and frameworks that can be used to perform efficient and effective data mining on large data sets. Vertical data mining strategy aims at addressing the scalability issues by organizing data in vertical layouts and conducting logical operations on vertical partitioned data instead of scanning the entire database horizontally in order to perform various data mining tasks.
Vertical data structures, vertical mining approaches and multi-relational vertical mining will be explored in detail to show how vertical data mining works.