Criteria Identification from Text Using Embeddings and Decision Templates

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Natural language processing systems struggle to effectively process and classify textual data due to variability in language and ambiguous terms, leading to challenges in identifying relevant criteria from textual data.

Innovation Solution

A system and method utilizing a computing device with a processor and memory, equipped with a language processing module, to identify and classify criteria through embeddings and dynamic decision templates, generating context-specific criteria for optimal decision-making.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If natural language processing is used to process textual data, then language understanding capability is improved, but ability to handle variability and ambiguity deteriorates

Engineering Contradiction:

Improvelanguage understanding capabilityVSAvoidability to handle variability and ambiguity

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The system segments the textual data processing into multiple stages: initial NLP processing to extract potential criteria, followed by separate verification and refinement steps that address ambiguity and variability independently, rather than attempting to handle all aspects in a single processing pass

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system introduces an intermediary verification mechanism that acts as a mediator between the NLP processing output and the final criteria identification. This intermediary layer checks for ambiguity and variability, resolving conflicts between language understanding capabilities and reliability requirements

Inventive Principle:

Principle #24Intermediary (Mediator)

2Productivity

If traditional NLP methods are used for criteria identification, then processing speed is maintained, but classification accuracy deteriorates

Engineering Contradiction:

Improveprocessing speedVSAvoidclassification accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The system performs preliminary actions by pre-processing textual data to identify and flag potentially ambiguous or variable terms before the main classification process. This preliminary step prepares the data for more accurate classification without requiring complete re-processing, thus maintaining processing speed while improving accuracy

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system dynamically adjusts processing depth based on detected data characteristics. When variability or ambiguity is detected, the system automatically increases verification steps and processing depth for those specific elements, while maintaining standard processing speed for clear, unambiguous criteria

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS12450439B1System and method for identifying one or more criteria from textual data

Publication Date: 2025.10.21 BH OPERATIONS LLC

AI summary

A system for identifying one or more criteria from textual data including at least a processor and a memory communicatively connected to the at least a processor, wherein the memory contains instructions configuring the at least a processor to receive a plurality of data, identify one or more sets of criteria from the plurality of data, classify each of the one or more sets of criteria using natural language processing module, compare the one or more sets of criteria and the individual profile based on the embeddings, generate a context-specific set of criteria as a function of the comparison between the one or more sets of criteria and the individual profile, and apply the context-specific set of criteria using a dynamic decision template to generate an outcome.