Personal Analytics and Privacy. An Individual and Collective Perspective (eBook, PDF)

First International Workshop, PAP 2017, Held in Conjunction with ECML PKDD 2017, Skopje, Macedonia, September 18, 2017, Revised Selected Papers
Redaktion: Guidotti, Riccardo; Abiteboul, Serge; Pedreschi, Dino; Monreale, Anna

• Format: PDF

Produktbeschreibung

This book constitutes the thoroughly refereed post-conference proceedings of the First International Workshop on Personal Analytics and Privacy, PAP 2017, held in Skopje, Macedonia, in September 2017.

The 14 papers presented together with 2 invited talks in this volume were carefully reviewed and selected for inclusion in this book and handle topics such as personal analytics, personal data mining and privacy in the context where real individual data are used for developing a data-driven service, for realizing a social study aimed at understanding nowadays society, and for publication purposes.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Springer-Verlag GmbH
• Seitenzahl: 159
• Erscheinungstermin: 4. Dezember 2017
• Englisch
• ISBN-13: 9783319719702
• Artikelnr.: 59890956

Inhaltsangabe

Your Privacy, My Privacy? On Leakage Risk Assessment in Online Social Networks.- From Self-Data to Self-Preferences: Towards Preference Elicitation in Personal Information Management Systems.- Assessing Privacy Risk in Retail Data.- Differential Privacy and Neural Networks.- Co-clustering for Differentially Private Synthetic Data Generation.- Evaluating the Impact of Friends in Predicting User's Availability in Online Social Networks.- Movement Behaviour Recognition for Water Activities.- Automatic Recognition of Public Transport Trips from Mobile Device Sensor Data and Transport Infrastructure Information.- Guess the Movie - Linking Facebook Pages to IMDb Movies.- Research on Online Digital Cultures - Community Extraction and Analysis by Markov and k-Means Clustering.- Churn Prediction Using Dynamic RFM-Augmented Node2vec.- Multi-scale Community Detection in Temporal Networks Using Spectral Graph Wavelets.- Influence Maximization-based Event Organization on Social Networks.