A volume in Contemporary Perspectives in Data Mining
Series Editors Kenneth D. Lawrence, New Jersey Institute of Technology
and Ronald K. Klimberg, Saint Joseph's University
The series, Contemporary Perspectives on Data Mining, is composed of blind refereed scholarly
research methods and applications of data mining. This series will be targeted both at the
academic community, as well as the business practitioner.
Data mining seeks to discover knowledge from vast amounts of data with the use of statistical
and mathematical techniques. The knowledge is extracted from this data by examining the
patterns of the data, whether they be associations of groups or things, predictions, sequential
relationships between time order events or natural groups.
Data mining applications are in marketing (customer loyalty, identifying profitable customers, instore
promotions, e-commerce populations), in business (teaching data mining, efficiency of the Chinese automobile industry, moderate
asset allocation funds), and techniques (veterinary predictive models, data integrity in the cloud, irregular pattern detection in a
mobility network and road safety modeling.)