AI Ad Content Recommendation Using Mutual Utility Functions

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Solution Overview

Problem

Existing decision support systems face challenges with information availability, reliability, and relevance, leading to suboptimal decisions due to high resource consumption, long temporal delays, and limited flexibility in handling multiple participant preferences and attributes.

Innovation Solution

A system and methodology that enables mutual evaluation of participant preferences through asymmetrical attribute surveys, utilizing conjoint analysis to derive utility functions, reducing resource consumption by minimizing computer cycles and storage needs, and facilitating efficient decision-making among multiple parties.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If comprehensive information is shared among decision participants, then decision reliability improves, but information processing time and resource consumption increase

Engineering Contradiction:

Improvedecision reliabilityVSAvoidinformation processing time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The patent segments information into structured attributes with defined hierarchies and relationships. Decision participants provide information in organized segments rather than unstructured comprehensive data, reducing processing time while maintaining reliability through systematic attribute-based evaluation.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system transforms unstructured information into structured parameters and attributes with defined relationships. By changing the form of information from unstructured to structured parameters, the system enables efficient processing while preserving decision reliability through consistent parameter evaluation.

Inventive Principle:

Principle #35Parameter changes

2Reliability

If comprehensive information is shared among decision participants, then decision reliability improves, but resource consumption increases

Engineering Contradiction:

Improvedecision reliabilityVSAvoidcomputational resource consumption

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

Information is segmented into structured attributes that can be processed efficiently. The hierarchical attribute structure allows the system to process only relevant segments of information needed for decision-making, reducing computational resource consumption while maintaining decision reliability.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system changes information into standardized parameters with defined relationships, enabling efficient computational processing. This parameter transformation reduces the computational complexity of evaluating comprehensive information while preserving the reliability needed for sound decisions.

Inventive Principle:

Principle #35Parameter changes

3Measurement precision

If detailed attribute information is collected from participants, then decision accuracy improves, but system complexity increases

Engineering Contradiction:

Improvedecision accuracyVSAvoidsystem complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent implements a universal attribute structure that can handle multiple types of decision information through a common framework. This multi-functional attribute system collects detailed information for accurate decisions while reducing system complexity by using standardized, reusable attribute definitions across different decision contexts.

Inventive Principle:

Principle #6Universality (Multi-functionality)

4Reliability

If information sharing is expanded among participants, then decision quality improves, but coordination difficulty increases

Engineering Contradiction:

Improvedecision qualityVSAvoidcoordination difficulty

Core Design Contradiction:

ReliabilityVSEase of operation

Solution Approach 1:

The system transforms participant information into standardized parameters with defined relationships, enabling efficient coordination. By changing information into a common parameter language, the system improves decision quality through comprehensive information sharing while reducing coordination difficulty through standardized interfaces.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS20260023986A1Artificial Intelligence Systems and Methods for Recommending Advertising Content to Users

Publication Date: 2026.01.22 BRAINTHROB LABORATORIES INC

AI summary

A system and methodology which can effectively provide decision makers with a better means of making decisions in a way that greatly improves the availability, reliability, and relevance of the information which they provide and use to make decisions. The system and methodology facilitates maximizing mutual utility in the context of a mutual decision between multiple users and groups of users identified generally as Parties and Counterparties and performs user specified actions based on meeting mutual threshold parameters. The system provides significant technical advantages over the prior art in that it uses helps Parties and Counterparties identify optimal arrangements and configurations with less errors, fewer computational cycles, less storage medium, and a smaller amount of time than would be possible using prior art systems.