Multi-Objective Score Ranking for Device Rendered Objects
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Solution Overview
Problem
Generating sets of device rendered objects is burdensome when multiple stakeholders have different interests, as existing solutions fail to efficiently determine relevant and recommended objects for users while ensuring stakeholder satisfaction and meeting objectives.
Innovation Solution
An apparatus and method that programmatically generate multiple objective scores for device rendered objects using unique objective models, adjust scores based on real-time factors, and rank objects for transmission to client devices, optimizing the selection based on user interface area size and interaction signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple objective models are used to generate scores for different stakeholders, then stakeholder satisfaction and user objectives are better met, but the system complexity and computational burden increase
Solution Approach 1:
The patent segments the recommendation system into multiple independent objective models, each responsible for a specific stakeholder's interests (user objectives, transaction objectives, currency value objectives). Each model generates scores independently, and these scores are then combined through weighting to form a comprehensive recommendation. This segmentation allows the system to address multiple stakeholder requirements without creating a single monolithic complex model.
Solution Approach 2:
The patent creates a universal scoring framework that serves multiple functions simultaneously. The same basic architecture of objective models and score combination mechanisms handles diverse stakeholder requirements (user satisfaction, transaction success, currency value optimization). This multi-functional approach allows a single system to meet multiple objectives without proportionally increasing complexity.
2Reliability
If device rendered object sets are generated to satisfy multiple stakeholder interests, then stakeholder objectives are met, but the generation process becomes burdensome and less efficient
Solution Approach 1:
The patent performs preliminary actions by pre-defining multiple objective models and their corresponding scoring mechanisms before the actual recommendation generation. The system pre-establishes the framework for evaluating user objectives, transaction objectives, and currency value objectives. When generating device rendered object sets, the system simply applies these pre-configured models and combines their scores, rather than creating evaluation criteria from scratch each time, thereby improving generation efficiency.
Solution Approach 2:
The patent uses parameter changes to balance multiple objectives efficiently. By adjusting the weights assigned to different objective scores (user objective weight, transaction objective weight, currency value objective weight), the system can flexibly prioritize different stakeholder interests based on current context without fundamentally changing the generation process. This parameter adjustment mechanism allows efficient adaptation to different scenarios while maintaining objective achievement.
3Ease of operation
If real-time adjustment factors are applied based on interaction signals, then user experience is optimized, but the computational requirements and processing time increase
Solution Approach 1:
The patent implements feedback mechanisms where interaction signals from users are continuously monitored and fed back into the scoring system. These interaction signals (clicks, views, purchases) serve as real-time feedback that adjusts the objective scores and recommendation rankings. The system processes this feedback efficiently by updating adjustment factors based on predefined rules and historical patterns, allowing user experience optimization without excessive processing time.
Data Source
AI summary
An apparatus, computer program product, and method are provided for predictive recommendations of device rendered objects using one or more objective models. In the context of a method, the method generates, for each device rendered object of a plurality of device rendered objects, a multiple objective score. The method also determines a real-time adjustment factor based in part on a received objective adjustment signal and generates, for each device rendered object of the plurality of device rendered objects, an adjusted multiple objective score based on the real-time adjustment factor. The method also generate a ranked device rendered object set, selects a subset of the ranked rendered object set, and transmits the ranked device rendered object subset to a client device associated with the user object of the user object objective, the subset configured for rendering within the user interface area of the client device.