Deep learning using activity graph to detect abusive user activity in online networks

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United States of America

PATENT NO 11991197
APP PUB NO 20230164157A1
SERIAL NO

17705146

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Abstract

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In an example embodiment, a deep learning algorithm is introduced that operates on a transition matrix formed from user activities in an online network. The transition matrix records the frequencies that particular transitions between paths of user activity have occurred (e.g., the user performed a login activity, which has one path in the network, and then performed a profile view action, which has another path in the network). Each transition matrix corresponds to a different user's activities.

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Patent Owner(s)

  • MICROSOFT TECHNOLOGY LICENSING, LLC.

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Boujelbene, Mariem Louisville, US 1 0
Chang, Jason Paul San Mateo, US 1 0
Chen, Ting Sunnyvale, US 194 4143
Verbus, James R San Mateo, US 2 0
Wang, Beibei Santa Clara, US 139 1204
Wu, Yi San Jose, US 222 2266

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