Übersicht			Auf mobile öffnen

Lieferstatus:	i.d.R. innert 5-10 Tagen versandfertig
Veröffentlichung:	Dezember 2018
Genre:	EDV / Informatik
	B / Business applications / computer science / Data Mining / Data Mining and Knowledge Discovery / Data structures (Computer science) / Data Structures and Information Theory / Data Warehousing / E-Commerce / e-Commerce and e-Business / E-commerce# business aspects / e-Commerce/e-business / Expert systems / knowledge-based systems / information architecture / Information Retrieval / Information Storage and Retrieval / Information theory / IT Operations / Maintenance & repairs / Management information systems / Management of Computing and Information Systems
ISBN:	9783030085865
EAN-Code:	9783030085865
Verlag:	Springer International Publishing
Einband:	Kartoniert
Sprache:	English
Dimensionen:	H 235 mm / B 155 mm / D 11 mm
Gewicht:	300 gr
Seiten:	192
Zus. Info:	Paperback
Bewertung:	Titel bewerten / Meinung schreiben

Inhalt:

With the growing popularity of ¿big datä, the potential value of personal data has attracted more and more attention. Applications built on personal data can create tremendous social and economic benefits. Meanwhile, they bring serious threats to individual privacy. The extensive collection, analysis and transaction of personal data make it difficult for an individual to keep the privacy safe. People now show more concerns about privacy than ever before. How to make a balance between the exploitation of personal information and the protection of individual privacy has become an urgent issue. In this book, the authors use methodologies from economics, especially game theory, to investigate solutions to the balance issue. They investigate the strategies of stakeholders involved in the use of personal data, and try to find the equilibrium. The book proposes a user-role based methodology to investigate the privacy issues in data mining, identifying four different types of users, i.e. four user roles, involved in data mining applications. For each user role, the authors discuss its privacy concerns and the strategies that it can adopt to solve the privacy problems.The book also proposes a simple game model to analyze the interactions among data provider, data collector and data miner. By solving the equilibria of the proposed game, readers can get useful guidance on how to deal with the trade-off between privacy and data utility. Moreover, to elaborate the analysis on data collector¿s strategies, the authors propose a contract model and a multi-armed bandit model respectively. The authors discuss how the owners of data (e.g. an individual or a data miner) deal with the trade-off between privacy and utility in data mining. Specifically, they study users¿ strategies in collaborative filtering based recommendation system and distributed classification system. They built game models to formulate the interactions among data owners, and propose learning algorithms to find the equilibria.