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Transparent Data Mining for Big and Small Data

Transparent Data Mining for Big and Small Data

Hardcover

Series: Studies in Big Data, Book 32

DatabasesGeneral LawProgramming

ISBN10: 3319540238
ISBN13: 9783319540238
Publisher: Springer Nature
Published: May 15 2017
Pages: 215
Weight: 1.12
Height: 0.56 Width: 6.14 Depth: 9.21
Language: English
Part I: Transparent Mining.- Chapter 1: The Tyranny of Data? The Bright and Dark Sides of Data-Driven Decision-Making for Social Good.- Chapter 2: Enabling Accountability of Algorithmic Media: Transparency as a Constructive and Critical Lens.- Chapter 3: The Princeton Web Transparency and Accountability Project.- Part II: Algorithmic solutions.- Chapter 4: Algorithmic Transparency via Quantitative Input Influence.- Chapter 5.- Learning Interpretable Classification Rules with Boolean Compressed Sensing.- Chapter 6: Visualizations of Deep Neural Networks in Computer Vision: A Survey.- Part III: Regulatory solutions.- Chapter 7: Beyond the EULA: Improving Consent for Data Mining.- Chapter 8: Regulating Algorithms Regulation? First Ethico-legal Principles, Problems and Opportunities of Algorithms.- Chapter 9: Algorithm Watch: What Role Can a Watchdog Organization Play in Ensuring Algorithmic Accountability?

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