Social Implications of Data Mining and Information Privacy: Interdisciplinary Frameworks and Solutions

As data mining is one of the most rapidly changing disciplines with new technologies and concepts continually under development, academicians, researchers, and professionals of the discipline need access to the most current information about the concepts, issues, trends, and technologies in this emerging field.

Social Implications of Data Mining and Information Privacy: Interdisciplinary Frameworks and Solutions serves as a critical source of information related to emerging issues and solutions in data mining and the influence of political and socioeconomic factors. An immense breakthrough, this essential reference provides concise coverage of emerging issues and technological solutions in data mining, and covers problems with applicable laws governing such issues.

The many academic areas covered in this publication include, but are not limited to:

• Agricultural data mining
• Basic principles of data mining
• Business Collaboration
• Data mining for automated building of teams
• Feature selection for web page classification
• Federal data mining programs
• Information ethics
• Information privacy and security for e-CRM
• Information security effectiveness theory
• Legal frameworks for data mining and privacy
• Machine learning techniques for Web page classification
• Metaphors and models for data mining
• Privacy in trajectory data
• Privacy preserving clustering
• Protection of privacy on the Web