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Covering research at the frontier of this field, PrivacyAware Knowledge Discovery: Novel Applications and New Techniques presents stateoftheart privacypreserving data mining techniques for application domains, such as medicine and social networks, that face the increasing heterogeneity and complexity of new forms of data. Renowned authorities from prominent organizations not only cover wellestablished resultsthey also explore complex domains where privacy issues are generally clear and well defined, but the solutions are still preliminary and in continuous development.Divided into seven parts, the book provides indepth coverage of the most novel reference scenarios for privacypreserving techniques. The first part gives general techniques that can be applied to various applications discussed in the rest of the book. The second section focuses on the sanitization of network traces and privacy in data stream mining. After the third part on privacy in spatiotemporal data mining and mobility data analysis, the book examines time series analysis in the fourth section, explaining how a perturbation method and a segmentbased method can tackle privacy issues of time series data. The fifth section on biomedical data addresses genomic data as well as the problem of privacyaware information sharing of health data. In the sixth section on web applications, the book deals with query log mining and web recommender systems. The final part on social networks analyzes privacy issues related to the management of social network data under different perspectives.While several new results have recently occurred in the privacy, database, and data mining research communities, a uniform presentation of uptodate techniques and applications is lacking. Filling this void, PrivacyAware Knowledge Discovery presents novel algorithms, patterns, and models, along with a significant collection of open problems for future investigation.
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birth defects, or other reproductive harm.
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