Ingredient Data Parsing System for Label Complexity

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Solution Overview

Problem

Complexity in ingredient information on food product labels makes it difficult for consumers and manufacturers to understand ingredient compositions, compliance with regulations, and comparison across products, leading to confusion and potential non-compliance.

Innovation Solution

An ingredient data management system that processes and parses text and graphics from product labels to identify constituent information, assign base attributes, and generate master attributes for display on user interfaces, allowing for improved understanding and compliance checking.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If detailed ingredient information is provided on product labels, then consumer information completeness is improved, but information complexity and difficulty to understand increases

Engineering Contradiction:

Improveingredient information completenessVSAvoidlabel information complexity

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The system segments ingredient information into hierarchical levels: raw ingredient data, processed ingredient attributes, and consumer-friendly presentations. This allows complete information to be stored and accessed while presenting simplified views to consumers through mobile applications and interactive interfaces.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces an intermediary processing system that sits between the complex ingredient data and the consumer. This system includes servers, databases, and software applications that automatically parse, standardize, and translate ingredient information into understandable formats, reducing the complexity burden on consumers while maintaining information completeness.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Adaptability or versatility

If standardized ingredient attributes are implemented across products, then comparability between products is improved, but data processing and management complexity increases

Engineering Contradiction:

Improveproduct comparabilityVSAvoiddata management complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system implements universal ingredient attribute standards that can be applied across multiple products and manufacturers. A centralized database structure stores standardized attributes (such as allergen information, nutritional content, sourcing details) that can be queried and compared across different products, enabling versatile product comparison while managing complexity through standardized protocols.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent transforms unstructured ingredient text into structured parameter-based data. By converting ingredient lists into standardized parameters (e.g., ingredient name, quantity, allergen flags, sourcing location), the system enables automated comparison and analysis while reducing management complexity through consistent data formats that can be processed algorithmically.

Inventive Principle:

Principle #35Parameter changes

3Measurement precision

If comprehensive ingredient detection and analysis is performed, then ingredient identification accuracy is improved, but processing time and computational resources increase

Engineering Contradiction:

Improveingredient identification accuracyVSAvoidprocessing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system performs preliminary actions by pre-processing and pre-categorizing ingredient information during product onboarding. Ingredient data is standardized, validated, and stored in structured formats before consumer queries, enabling rapid retrieval and accurate identification without requiring extensive processing at the point of consumer interaction.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent replaces manual ingredient analysis with automated computational systems. Optical character recognition (OCR) technology captures ingredient text from labels, and machine learning algorithms automatically parse and categorize the information, substituting manual processing with efficient computational methods that maintain high accuracy while reducing processing time.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS10699280B2Information management system for product ingredients that produces hybrid data offerings combining product information data and analytic data

Publication Date: 2020.06.30 NIELSEN CONSUMER LLC

AI summary

An ingredient data system that ingests text and graphics of product labels associated with consumer products generally includes a memory having instructions stored thereon; and at least one processor to execute the instructions to transmit via a network a representation of a label view to a user interface on a client computing device that displays one or more of the master attributes associated with the first request, at least a portion of each of the images of one or more of the product labels of the consumer products having the one or more master attributes associated with the first request and at least a portion of the sales history, and at least a portion of each of the images of one or more of the product labels associated with the related consumer products and at least a portion of a sales history.