Composite Object Valuation Using Hierarchical Relationship Processing

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Solution Overview

Problem

Computing systems face challenges in efficiently processing and computing values for inter-related objects with changing rules and restrictions, leading to inefficiencies and redundancy in determining optimal solutions.

Innovation Solution

The system identifies and selects optimal solutions by leveraging object relationships and external data sources to corroborate the veracity of composite object values, using a hierarchical approach to prioritize and iteratively process relationships, thereby reducing the need to calculate all possible combinations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If the system processes all possible combinations of inter-related objects to determine optimal solutions, then the accuracy and completeness of object value computation is improved, but the processing time and computational complexity increase significantly

Engineering Contradiction:

Improveaccuracy of object value computationVSAvoidprocessing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent segments the computation process by dividing objects into base objects and composite objects. Base objects are computed directly from data, while composite objects are computed from their constituent base objects. This segmentation allows the system to process only necessary combinations rather than all possible combinations, reducing computational complexity while maintaining accuracy.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system performs preliminary computation of base object values before computing composite object values. By pre-computing and storing base object values, the system avoids redundant calculations when computing composite objects, significantly reducing processing time while ensuring accurate results through a structured computation sequence.

Inventive Principle:

Principle #10Preliminary action

2Reliability

If the system computes values for all inter-related objects using multiple procedures and routines, then the comprehensiveness of the solution is improved, but the device complexity and processing overhead increase

Engineering Contradiction:

Improvecompleteness of solutionVSAvoidsystem complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent segments the solution space into distinct computation paths: direct computation for base objects and derived computation for composite objects. This segmentation simplifies the system architecture by establishing clear computation rules for each object type, reducing system complexity while ensuring comprehensive coverage of all inter-related objects through their respective computation paths.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system applies partial computation by focusing only on the necessary computation paths rather than exhaustively processing all possible object relationships. Base objects require full computation from data, while composite objects require computation only from their specific constituent base objects, avoiding unnecessary processing of unrelated object combinations and simplifying the overall system.

Inventive Principle:

Principle #16Partial or excessive action

3Adaptability or versatility

If the system iteratively processes changing rules and restrictions for inter-related objects, then the adaptability to dynamic environments is improved, but the processing efficiency decreases

Engineering Contradiction:

Improveadaptability to changing rulesVSAvoidprocessing efficiency

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

The patent implements dynamic computation by allowing the system to adaptively determine computation paths based on object relationships and data availability. When base object values change, the system dynamically triggers recomputation of affected composite objects only, rather than reprocessing all objects. This dynamic approach maintains adaptability to changing rules while preserving processing efficiency through selective updates.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system employs feedback mechanisms where computation results of base objects feed into composite object computations. When rules or data change, the feedback loop identifies which composite objects are affected and triggers only those specific recomputations. This feedback-driven approach enables the system to adapt to changing conditions efficiently by processing only the necessary subset of objects.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS12596723B2Dynamic valuation system using object relationships and composite object data

Publication Date: 2026.04.07 CHICAGO MERCANTILE EXCHANGE INC

AI summary

The disclosed embodiments relate to systems and methods for generating an optimal solution for determining a value for one or more base data objects. A plurality of solutions include one or more composite data objects transacted by a transaction system processor. The composite data objects include the one or more base data objects. An optimal solution is generated by using data indicative of a level of activity and a number of sources for each of the plurality of composite data objects.