Transparent data mining for big and small data / Tania Cerquitelli, Daniele Quercia, Frank Pasquale, editors.
Cerquitelli, Tania.; Quercia, Daniele.; Pasquale, Frank.
2017
QA76.9.D343
Available Online

Linked e-resources

Linked Resource Online Access
Concurrent users Unlimited
Authorized users Authorized users
Document Delivery Supplied Can lend chapters, not whole ebooks

Details

Title Transparent data mining for big and small data / Tania Cerquitelli, Daniele Quercia, Frank Pasquale, editors.
ISBN 9783319540245 (electronic book)
3319540246 (electronic book)
3319540238
9783319540238
DOI https://doi.org/10.1007/978-3-319-54024-5
Published Cham : Springer International Publishing : Imprint: Springer, 2017.
Language English
Description 1 online resource (xv, 215 pages) : illustrations.
Item Number 10.1007/978-3-319-54024-5 doi
Call Number QA76.9.D343
Dewey Decimal Classification 006.3/12
004
Access Note Access limited to authorized users.
Source of Description Description based on print version record.
Added Author Cerquitelli, Tania.
Quercia, Daniele.
Pasquale, Frank.
Series Studies in big data ; v. 11.
Available in Other Form Print version: 9783319540238
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
All Resources
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?

Browse Subjects

Show more subjects...

Statistics

from
to
Export