Invention Grant
- Patent Title: Similarity learning-based device attribution
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Application No.: US15814167Application Date: 2017-11-15
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Publication No.: US11042810B2Publication Date: 2021-06-22
- Inventor: Shalin S. Shah , Nicholas Scott Eggert , Ramasubbu Venkatesh
- Applicant: Target Brands, Inc.
- Applicant Address: US MN Minneapolis
- Assignee: Target Brands, Inc.
- Current Assignee: Target Brands, Inc.
- Current Assignee Address: US MN Minneapolis
- Agency: Merchant & Gould P.C.
- Main IPC: G06N7/00
- IPC: G06N7/00 ; H04L29/08 ; G06F17/18 ; G06N20/00

Abstract:
Methods and systems for attributing browsing activity from two or more different network-connected devices to a single user are disclosed. In one aspect, cookies generated by the browsing activity of different unidentified devices at a website are received. A random forest classifier trained on probabilities output from a Gaussian mixture model is applied to the unidentified cookies to determine a probability that two different cookies were generated by the same user. In some embodiments, personalized content is then delivered to the user based on the characteristics of the paired cookies.
Public/Granted literature
- US20190149626A1 SIMILARITY LEARNING-BASED DEVICE ATTRIBUTION Public/Granted day:2019-05-16
Information query
IPC分类:
G | 物理 |
G06 | 计算;推算或计数 |
G06N | 基于特定计算模型的计算机系统 |
G06N7/00 | 基于特定数学模式的计算机系统 |