Dynamic Content Distribution via User Profile Association

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Solution Overview

Problem

Existing content distribution methods fail to dynamically adapt multimedia content to individual user profiles, often relying solely on contextual information from the content itself and broadcasting the same secondary content to all users, without considering user-specific interests or preferences.

Innovation Solution

A method that collects information from users after content distribution, determines association data based on user profiles, and dynamically selects and associates secondary content with the primary content based on user profiles, allowing for temporal and spatial integration of user-specific multimedia content during distribution.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If the same second content is broadcast to all users based solely on contextual information from the first content, then the content distribution process is simple and efficient, but the content cannot be adapted to individual user profiles or preferences

Engineering Contradiction:

Improvecontent adaptation to user profileVSAvoiddistribution system complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system pre-collects user profile information and preferences before content distribution occurs. This preliminary data collection enables the distribution system to quickly match users with relevant second content without requiring complex real-time analysis during the distribution process itself

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent introduces an intermediary component that acts as a bridge between the first content and second content selection. This intermediary processes user profile information and contextual information to determine appropriate associations, separating the complexity of profile analysis from the content distribution mechanism

Inventive Principle:

Principle #24Intermediary (Mediator)

2Measurement precision

If contextual information is extracted from different parts of the first content to select second content, then the relevance of second content to user interests improves, but the complexity of determining appropriate content associations increases

Engineering Contradiction:

Improvecontent association accuracyVSAvoidassociation determination complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system segments the first content into multiple parts and extracts contextual information from each segment independently. This segmentation allows for more precise matching of second content to specific portions of the first content that are most relevant to user interests, while the modular approach manages the complexity through structured processing

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Different parts of the first content are analyzed with different contextual extraction rules based on their specific characteristics. This local quality approach ensures that each segment is processed appropriately for its content type, improving overall association accuracy while maintaining manageable complexity through targeted analysis

Inventive Principle:

Principle #3Local quality

3Reliability

If user feedback and information are collected after content distribution to update association data, then the precision and reliability of content associations improve over time, but the time required for the distribution process increases

Engineering Contradiction:

Improveassociation data reliabilityVSAvoiddistribution process time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system implements a feedback mechanism where user responses to distributed content are collected and used to update association data for future distributions. This feedback loop continuously improves the reliability of content associations by learning from actual user behavior and preferences observed during and after distribution

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

While feedback collection occurs after distribution, the system performs preliminary processing of this feedback data to quickly update association rules. This preliminary processing of feedback minimizes the time impact on subsequent distributions while still capturing the reliability improvements from user responses

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentEP2200258B1Method for distributing content to a user

Publication Date: 2014.11.19 ORANGE SA

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AI summary

The invention relates to a method of distributing a first piece of content (C1) to a first user (U2), comprising: - a step of collecting information relating to at least a part of the first piece of content developed following a distribution of the first piece of content to second users (U1); - a step of determining an association data relating to the first piece of content from the information collected and the respective profiles of said second users, said association data associating, for a given user profile, at least a part of the first piece of content and a second piece of content to be associated, - a step of determining a second piece of content (C2) to be associated with a part of the first piece of content according to a profile of the first user by means of said association data relating to the first piece of content;- a distribution stage of the first content, during which the second determined content is associated with said part of said first content.;