Ashwani Kumar (ed.); Iztok Fister Jr. (ed.); P. K. Gupta (ed.); Johan Debayle (ed.); Zuopeng Justin Zhang (ed.); Moh Usman Springer (2022) Pehmeäkantinen kirja
Justin B. Bullock; Yu-Che Chen; Johannes Himmelreich; Valerie M. Hudson; Anton Korinek; Matthew M. Young; Baobao Zhang Hurst&Co. (2024) Kovakantinen kirja
Hannelore Lee-Jahnke; Justine Ning DING; Erin Rui LI; Zhengren LI; Irene A. Zhang Peter Lang AG, Internationaler Verlag der Wissenschaften (2024) Pehmeäkantinen kirja
Springer Sivumäärä: 280 sivua Asu: Kovakantinen kirja Julkaisuvuosi: 2024, 28.08.2024 (lisätietoa) Kieli: Englanti
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.
