Abstract
This paper aims to simultaneously consider two inseparable issues for privacy setting recommendation: (1) sensitiveness of visual content of the images being shared; and (2) trustworthiness of users being granted. First, an object-based approach is developed for image content sensitiveness (privacy) representation. Secondly, the users on a social network are clustered into a set of representative social groups to generate a discriminative dictionary for user trustworthiness characterization. Finally, a tree classifier is trained hierarchically to recommend appropriate privacy settings for image sharing.
Recommended Citation
J. Yu et al., "Privacy Setting Recommendation for Image Sharing," Proceedings - 16th IEEE International Conference on Machine Learning and Applications, ICMLA 2017, pp. 726 - 730, Institute of Electrical and Electronics Engineers, Jan 2017.
The definitive version is available at https://doi.org/10.1109/ICMLA.2017.00-73
Department(s)
Computer Science
Keywords and Phrases
Image Sharing; Privacy Recommendation; Social Network; Tree Classifier
International Standard Book Number (ISBN)
978-153861417-4
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
01 Jan 2017
