Viewing Preference Access Control for Personalized Recommendations

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Solution Overview

Problem

Users lack control over how their media consumption data is used by content providers, leading to inaccurate recommendations and potential contamination across different devices and times, and existing systems fail to securely manage data sharing between providers.

Innovation Solution

A system that allows users to selectively grant access to their consumption data by content providers using a database of records with access indications and a distributed ledger, enabling secure token management with public-key encryption.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If content providers access user consumption data to generate recommendations, then recommendation personalization is improved, but user control over data sharing deteriorates

Engineering Contradiction:

Improverecommendation personalizationVSAvoiduser control over data sharing

Core Design Contradiction:

Measurement precisionVSEase of operation

Solution Approach 1:

The system segments user consumption data into discrete database records, each with independent access control indicators. Users can selectively grant or deny access to specific records based on content items, devices, or time periods, enabling granular control over data sharing while maintaining personalized recommendations.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The access control system is dynamic, allowing users to modify access indications for different database records based on changing preferences, devices, or time periods. The system adapts access permissions in real-time based on user actions, enabling flexible control over data sharing without compromising recommendation quality.

Inventive Principle:

Principle #15Dynamics

2Adaptability or versatility

If content providers use all user viewing data for recommendations, then recommendation coverage is improved, but data contamination across different contexts worsens

Engineering Contradiction:

Improverecommendation coverageVSAvoiddata contamination

Core Design Contradiction:

Adaptability or versatilityVSObject-generated harmful factors

Solution Approach 1:

The system applies local quality by differentiating access permissions based on specific contexts such as device type, time period, and content category. Each database record can have customized access indications that prevent certain data from being used for recommendations in specific contexts, thereby eliminating contamination while maintaining overall recommendation coverage.

Inventive Principle:

Principle #3Local quality

3Ease of operation

If users are provided with granular control options for each database record, then user autonomy is improved, but system complexity worsens

Engineering Contradiction:

Improveuser autonomyVSAvoidsystem complexity

Core Design Contradiction:

Ease of operationVSDevice complexity

Solution Approach 1:

The system implements universality by providing a unified access control interface that handles multiple scenarios (different devices, time periods, content types) through a single consistent mechanism. Users interact with a standardized set of options that work across all database records, simplifying the user experience while maintaining granular control capabilities.

Inventive Principle:

Principle #6Universality (Multi-functionality)

4Measurement precision

If content providers aggregate user data across all devices and times, then recommendation accuracy is improved, but user privacy protection worsens

Engineering Contradiction:

Improverecommendation accuracyVSAvoiduser privacy violation

Core Design Contradiction:

Measurement precisionVSObject-affected harmful factors

Solution Approach 1:

The system extracts and isolates specific database records that users wish to share with content providers, separating them from the broader dataset. By selectively transmitting only the extracted records that have access indications permitting content provider access, the system maintains recommendation accuracy for relevant content while protecting user privacy by excluding sensitive or unwanted data.

Inventive Principle:

Principle #2Taking out (Extraction)

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

Users can control data sharing with granular precision, ensuring tailored recommendations based on device and time, while maintaining data security and privacy.

Implementation Method 1

a distributed ledger, enabling secure token management with public-key encryption

Methodology Applied

Scientific EffectPublic-key encryption:

Data Source

PatentUS20260017398A1User-controlled viewing preferences

Publication Date: 2026.01.15 ADEIA GUIDES INC

AI summary

Systems and methods are described to a database comprising multiple database records, where each database record comprises an attribute of a content item consumed by a user and an indication of a user device used by the user to consume the content item, and is associated with an indication of whether a content provider should be granted access to the respective database record. An option to modify whether or not the content provider should be granted access to the respective database record is provided for each database record of the database records, and each database record that is associated with an indication that the content provider should be granted access is transmitted to the content provider, to enable the content provider to generate and transmit a content recommendation based on at least one of the database records transmitted to the content provider.