Tree Data Structure for Unified Asset Classification

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Solution Overview

Problem

Inefficient data storage and access within organizations due to inconsistencies in data organization, classification, and access across different departments, leading to labor-intensive and costly data governance.

Innovation Solution

A method involving a machine learning model that defines a tree data structure with leader and follower subtrees, linked to a hierarchical classification structure, to map assets and efficiently locate them based on query attributes, optimizing storage and access.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If multiple departments store data in different data structures with inconsistent classifications, then each department can organize data according to its own needs, but data access speed decreases and computing power requirements increase

Engineering Contradiction:

Improvedepartment-specific data organization flexibilityVSAvoiddata access speed

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

The patent merges multiple department-specific data structures into a single unified tree data structure. Each department can still access data according to its own classification needs through the unified structure, eliminating redundancy while maintaining organizational flexibility. This resolves the contradiction by combining multiple perspectives into one consistent framework that speeds up access across the entire organization.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The unified tree data structure serves multiple departments simultaneously with a single consistent classification system. The structure is designed to accommodate various departmental needs (legal, finance, HR, etc.) while providing uniform access mechanisms. This multi-functional design eliminates the need for separate departmental structures, thereby improving overall productivity without sacrificing adaptability.

Inventive Principle:

Principle #6Universality (Multi-functionality)

2Adaptability or versatility

If multiple departments maintain separate data classification structures, then each department can use its own classification methodology, but data governance becomes labor intensive and costly

Engineering Contradiction:

Improvedepartment-specific classification methodologyVSAvoiddata governance complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent consolidates multiple departmental classification methodologies into a single unified tree data structure that serves all departments. This merging reduces the complexity of data governance by eliminating the need to maintain and synchronize multiple separate classification systems. The unified structure preserves the essential classification needs of each department while presenting a single manageable framework.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The machine learning model automatically classifies data into the unified tree structure without requiring manual governance interventions. The system self-manages the classification process, automatically assigning data to appropriate nodes based on departmental requirements and data characteristics. This automation dramatically reduces the labor-intensive nature of data governance while maintaining adaptability to different departmental needs.

Inventive Principle:

Principle #25Self-service

3Adaptability or versatility

If inconsistent data classification is used across the organization, then data can be stored in multiple locations, but computing power and expense increase

Engineering Contradiction:

Improvedata storage location flexibilityVSAvoidcomputing power consumption

Core Design Contradiction:

Adaptability or versatilityVSUse of energy by moving object

Solution Approach 1:

The patent merges multiple data storage locations into a single unified tree data structure that organizes data efficiently. This consolidation reduces the computing power required for data management by eliminating redundant classification and indexing operations that would be needed if maintaining separate departmental structures. The unified structure provides flexible access to data from any location while consuming significantly fewer computational resources.

Inventive Principle:

Principle #5Merging (Combining)

Data Source

PatentUS11720600B1Methods and apparatus for machine learning to produce improved data structures and classification within a database

Publication Date: 2023.08.08 ENTERPRISE E SUPPORT INC

AI summary

In some embodiments, a method includes extracting metadata of a set of assets and providing the metadata to a machine learning model to define a tree data structure including a leader subtree and a follower subtree that is dependent upon a portion of a hierarchical classification structure of the leader subtree. The method further includes matching the metadata to attributes assigned to classification nodes within the tree data structure to map the set of assets into data nodes of the tree data structure. The method further includes parsing a query to traverse the tree data structure to locate an asset based at least in part on the query attribute and at least one of the attributes assigned to the classification nodes, and, after and/or in response to parsing the query, sending a signal representing the asset and/or a location of the asset.