A Differential Privacy Mechanism that Accounts for Network Effects for Crowdsourcing Systems
A Differential Privacy Mechanism that Accounts for Network Effects for Crowdsourcing Systems
About this item
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Author / Creator
Publisher
San Francisco: AI Access Foundation
Journal title
Language
English
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Publication information
Publisher
San Francisco: AI Access Foundation
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Scope and Contents
Contents
In crowdsourcing systems, it is important for the crowdsource campaign initiator to incentivize users to share their data to produce results of the desired computational accuracy. This problem becomes especially challenging when users are concerned about the privacy of their data. To overcome this challenge, existing work often aims to provide user...
Alternative Titles
Full title
A Differential Privacy Mechanism that Accounts for Network Effects for Crowdsourcing Systems
Authors, Artists and Contributors
Author / Creator
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Record Identifier
TN_cdi_proquest_journals_2553250818
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2553250818
Other Identifiers
ISSN
1076-9757
E-ISSN
1076-9757,1943-5037
DOI
10.1613/jair.1.12158
