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》 资源 》论文》a group based personalized model for image privacy classification and labeling

a group based personalized model for image privacy classification and labeling

2019-11-04 | |  59 |   42 |   0
Abstract We address machine prediction of an individual’s label (private or public) for a given image. This problem is difficult due to user subjectivity and inadequate labeled examples to train individual, personalized models. It is also time and space consuming to train a classifier for each user. We propose a Group-Based Personalized Model for image privacy classification in online social media sites, which learns a set of archetypical privacy models (groups), and associates a given user with one of these groups. Our system can be used to provide accurate “early warnings” with respect to a user’s privacy awareness level.

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