Year: 2014
Type: article
Abstract: The enormous data sharing and data availability on the Internet pro-vides opportunities for new services tailored to extract, search, ag-gregate, and mine data in meaningful ways, At the same time, it poses challenges with regards to data privacy. This paper offers in-sight into this problem, focusing on current relevant research and potential areas of synergy between the information retrieval com-munity and the privacy community. We then analyze example pub-licly shared data and discuss the types of data that can be extracted, the methods used for extracting them, and the implications for in-dividuals who share personal information. 1.
Authors: Sicong Zhang, Grace Hui Yang, Lisa Singh
Institution: Georgetown University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funder: National Science Foundation
OpenAlex ID: W2295841041