公开(公告)号：US10817618B2

公开(公告)日：2020-10-27

申请号：US16041182

申请日：2018-07-20

Applicant: Adobe Inc.

Inventor： Ankur Garg ,  Kritin Kesav Sai Sathi ,  Kirnesh Nandan ,  Iftikhar Ahamath Burhanuddin ,  Aditya Prakash

IPC: H04L29/06 ,  G06F21/62 ,  G06F21/60 ,  G06F16/9535

Abstract: In implementations of a recommendation system based on individualized privacy settings, a computing device maintains user profiles of information and recommendations associated with users of the recommendation system. The computing device includes a recommendation module that is implemented to receive a privacy level selection for a type of items corresponding to a user profile in the system. The recommendation module can determine a privacy setting for a user associated with the user profile, where the privacy setting is individualized for the user in context of the type of items with an algorithmic noise function utilized to obfuscate a proportional level of the information associated with the user and the type of items based on the received privacy level selection. The recommendation module can also generate recommendations of relevant items for the user based on the determined privacy setting as individualized for the user in context of the type of items.

公开(公告)号：US20200026876A1

公开(公告)日：2020-01-23

申请号：US16041182

申请日：2018-07-20

Applicant: Adobe Inc.

Inventor： Ankur Garg ,  Kritin Kesav Sai Sathi ,  Kirnesh Nandan ,  Iftikhar Ahamath Burhanuddin ,  Aditya Prakash

IPC: G06F21/62 ,  G06F21/60 ,  G06F17/30

Abstract: In implementations of a recommendation system based on individualized privacy settings, a computing device maintains user profiles of information and recommendations associated with users of the recommendation system. The computing device includes a recommendation module that is implemented to receive a privacy level selection for a type of items corresponding to a user profile in the system. The recommendation module can determine a privacy setting for a user associated with the user profile, where the privacy setting is individualized for the user in context of the type of items with an algorithmic noise function utilized to obfuscate a proportional level of the information associated with the user and the type of items based on the received privacy level selection. The recommendation module can also generate recommendations of relevant items for the user based on the determined privacy setting as individualized for the user in context of the type of items.