Privacy Preservation using Intelligent Techniques - Geetha Mary Amalanathan
-35% koodilla BOOKS
Toimitus 12-18 arkipäivässä
30 päivän palautusoikeus
Privacy Preserving Data Mining (PPDM) is an active research area which deals with generation of knowledge without revealing user identity or sensitive information. Real world data is made up of vague and uncertain data and spans to many universe and granules, which were not considered in PPDM. The focus of this book is towards entrench PPDM techniques in intelligent techniques like fuzzy set theory, rough s ... Täydellinen kuvaus
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Kuvaus
Privacy Preserving Data Mining (PPDM) is an active research area which deals with generation of knowledge without revealing user identity or sensitive information. Real world data is made up of vague and uncertain data and spans to many universe and granules, which were not considered in PPDM. The focus of this book is towards entrench PPDM techniques in intelligent techniques like fuzzy set theory, rough set theory and association rule mining, over vague and imprecise data. Studies were conducted based on varying real life scenarios and designing methods to suit to those needs were proposed and proved through theoretically and experimentally. This book is produced from many theories, proofs, experiments and studies, which were presented in a simple and understandable style. This book would serve as a major source of knowledge for researchers in the area of PPDM, data mining and rough set theory.
Lisätietoja
| Kirjoittaja | Geetha Mary Amalanathan |
|---|---|
| Julkaisija | LAP LAMBERT Academic Publishing |
| Julkaisuvuosi | 2016 |
| Kannen tyyppi | Pehmeäkantinen |
| EAN | 9783330002647 |