ShareGraph Social Graph Node Identification via Device Fingerprinting

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Solution Overview

Problem

Building a social graph for the open Web is challenging due to anonymous users and privacy concerns, making it difficult to track sharing activities and personalize content and advertisements effectively.

Innovation Solution

The ShareGraph system tracks and models user connections based on sharing activities across the open Web, using anonymous user IDs and proprietary algorithms to create a weighted multigraph that represents real connections and interests, allowing for precise ad targeting without personally identifiable information.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If user information is collected for social graph building, then ad targeting accuracy is improved, but user privacy protection deteriorates

Engineering Contradiction:

Improvead targeting accuracyVSAvoiduser privacy exposure

Core Design Contradiction:

Measurement precisionVSObject-affected harmful factors

Solution Approach 1:

The patent uses device fingerprints as copies or representations of user identity instead of collecting actual personal information. The system creates a pseudonymous identifier based on device characteristics that can track user behavior and build social graphs without exposing real user identities, thus maintaining ad targeting accuracy while protecting privacy.

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The patent introduces device fingerprints as an intermediary between the user and the tracking system. Instead of directly collecting personal information, the system uses these fingerprint identifiers as a mediator to track sharing activities and build social connections, enabling accurate ad targeting without direct access to sensitive user data.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Object-affected harmful factors

If anonymous user tracking is implemented, then privacy protection is improved, but user identification accuracy deteriorates

Engineering Contradiction:

Improveuser privacy protectionVSAvoiduser identification accuracy

Core Design Contradiction:

Object-affected harmful factorsVSMeasurement precision

Solution Approach 1:

The patent changes the parameters used for identification from personal information to device characteristics. By using multiple device parameters (browser type, screen resolution, installed fonts, etc.) to create composite fingerprints, the system maintains identification accuracy while preserving user anonymity through pseudonymous identifiers.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent creates composite device fingerprints by combining multiple device characteristics and parameters into a single identifying profile. This composite approach uses various device attributes (hardware and software features) to generate unique identifiers that accurately distinguish users without requiring personal information.

Inventive Principle:

Principle #40Composite materials

3Adaptability or versatility

If sharing activity tracking is implemented, then content personalization is improved, but system complexity deteriorates

Engineering Contradiction:

Improvecontent personalizationVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent performs preliminary actions by pre-establishing device fingerprints and pseudonymous identifiers before tracking sharing activities. This allows the system to automatically recognize and track user sharing behavior across different websites without requiring complex real-time processing, simplifying the overall system architecture while enabling content personalization.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS9779416B2Using fingerprinting to identify a node in a social graph of sharing activity of users of the open web as representing a particular person

Publication Date: 2017.10.03 R1DEMAND LLC

AI summary

A social graph is built which includes interactions, sharing activity, and connections between the users of the open Web and can be used to improve ad targeting and content personalization. Personally identifiable information is not collected. The sharing activity can include receiving first activity information for a sender of a message to a recipient by a collection resource at a Web site, the collection resource adding a link to the message, and receiving second activity information when the recipient accesses the link. The first or second activity information can include a cookie, which can be used to identify a node in a social graph as being representative of a particular person or user. When a match is not found, a fingerprinting approach can be performed using attributes, such as device identifiers; IP addresses; operating systems; browsers types; browser versions; or user navigational, geo-temporal, or behavioral patterns.