Discovering Structural Patterns in Telecommunications Data
Andi Baritchi, Diane J. Cook, Lawrence B. Holder · 2000
With the increasing amount and complexity of data being collected, there is an urgent need to create automated techniques for mining the data. In particular, data being generated and stored by telecom companies overwhelms scientists' ability to manually discover patterns in the data. Because much of this data is structural in nature, or composed of parts and relations between the parts, linear attribute-value based algorithms will not capture all of the intricacies of the data. Hence, there exists a need to develop scalable tools to analyze and discover concepts in structural databases. Introduction New technology and new laws are changing the telecommunications industry at a blinding rate. New methods of mining the data are needed to understand and control these changes. Because the amount of collected data far exceeds the ability to manually search for and interpret patterns in the data, there is a need to improve the discovery of knowledge in these large databases. Equi...