ISBN13: | 9780387879659 |
ISBN10: | 038787965X |
Binding: | Hardback |
No. of pages: | 280 pages |
Size: | 235x155 mm |
Language: | English |
Illustrations: | 20 Illustrations, black & white |
0 |
Theory of computing, computing in general
System analysis, system planning
Data management in computer systems
Hardware and operating systems in general
Computer programming in general
Database management softwares
Office softwares, spreadsheets
Privacy, data security
More books in the field of economy
Secure Data Mining
EUR 71.64
Click here to subscribe.
This book provides solutions to the problem of data mining without compromising data privacy. This professional book is designed for practitioners and researchers in industry, as well as a secondary textbook for advanced-level students in computer science.
Data mining is a process to extract useful knowledge from large amounts of data. To conduct data mining, we often need to collect data. However, privacy concerns may prevent people from sharing the data and some types of information about the data. How we conduct data mining without breaching data privacy presents a challenge.
Secure Data Mining provides solutions to the problem of data mining without compromising data privacy. This professional book is designed for practitioners and researchers in industry, as well as a secondary textbook for advanced-level students in computer science.
Preface.- Introduction.- Literature Review.- Fundamental Security and Privacy.- Privacy-Preserving Association Rule Mining.- Privacy-Preserving Sequential Pattern Mining.- Privacy-Preserving Naive Bayesian Classification.- Privacy-Preserving Decision Tree Classification.- Privacy-Preserving k-Nearest Neighbor Classification.- Privacy-Preserving Support Vector Machine Classification.- Privacy-Preserving k-Mean Clustering.- Privacy-Preserving k-Medoids Clustering.- Other Selected Topics.- Conclusion and Future Work.- Index.