TY - BOOK ID - 79534620 TI - Association Rule Hiding for Data Mining AU - Gkoulalas-Divanis, Aris AU - Verykios, Vassilios S AU - SpringerLink (Online service) PY - 2010 SN - 9781441965691 9781441965684 9781461426059 9781441965707 PB - Boston MA Springer US DB - UniCat KW - Complex analysis KW - Production management KW - Computer science KW - Programming KW - Computer architecture. Operating systems KW - Information systems KW - Artificial intelligence. Robotics. Simulation. Graphics KW - Computer. Automation KW - betrouwbaarheid KW - complexe analyse (wiskunde) KW - applicatiebeheer KW - apps KW - informatica KW - informatiesystemen KW - database management KW - informatietechnologie KW - algoritmen KW - KI (kunstmatige intelligentie) KW - architectuur (informatica) UR - https://www.unicat.be/uniCat?func=search&query=sysid:79534620 AB - Privacy and security risks arising from the application of different data mining techniques to large institutional data repositories have been solely investigated by a new research domain, the so-called privacy preserving data mining. Association rule hiding is a new technique on data mining, which studies the problem of hiding sensitive association rules from within the data. Association Rule Hiding for Data Mining addresses the optimization problem of hiding  sensitive association rules which due to its combinatorial nature admits a number of heuristic solutions that will be proposed and presented in this book. Exact solutions of increased time complexity that have been proposed recently are also presented as well as a number of computationally efficient (parallel) approaches that alleviate time complexity problems, along with a discussion regarding unsolved problems and future directions. Specific examples are provided throughout this book to help the reader study, assimilate and appreciate the important aspects of this challenging problem. Association Rule Hiding for Data Mining is designed for researchers, professors and advanced-level students in computer science studying privacy preserving data mining, association rule mining, and data mining. This book is also suitable for practitioners working in this industry. ER -