Text Intention Reader With Regex Entailment Scoring
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Solution Overview
Problem
The degradation of human brain-sensory systems in inferring intentions from written text communications due to the absence of multiple information channels present in face-to-face interactions makes it difficult to accurately assess intentions in business transactions.
Innovation Solution
A system, I-Read, utilizing a cloud-based hub with an intention database and neural networks to process textual communications, identifies regexes and determines degrees of entailment between test regexes and IIRs to infer intentions related to specific topics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If written text communication is used, then communication efficiency and recordability are improved, but intention inference accuracy deteriorates due to loss of multichannel information
Solution Approach 1:
The patent introduces an intermediary system (intention inference system) that mediates between written text communication and intention understanding. This system compensates for the loss of multichannel information by using NLP techniques, contextual analysis, and pattern recognition to infer intentions that would normally be conveyed through tone, facial expressions, and body language in face-to-face communication.
Solution Approach 2:
The patent replaces the mechanical/sensory system of human face-to-face communication (which naturally processes multiple channels simultaneously) with a computational system using natural language processing, machine learning models, and text analysis algorithms. This substitution enables automated intention inference from text-only communications.
2Ease of operation
If written text communication is used, then communication convenience and scalability are improved, but intention assessment accuracy deteriorates
Solution Approach 1:
An intermediary intention inference system is introduced to bridge the gap between convenient text-based communication and accurate intention assessment. The system acts as a mediator that enhances text communications with inferred intention data, allowing users to maintain communication convenience while gaining deeper insight into the sender's intentions through automated analysis.
3Measurement precision
If human brain-sensory systems are used for face-to-face communication, then intention inference accuracy is improved, but communication scalability and accessibility deteriorate
Solution Approach 1:
The patent replaces the biological brain-sensory system with an artificial intelligence system that can process and infer intentions from text communications. This substitution maintains high accuracy in intention inference while dramatically improving scalability, as the AI system can simultaneously analyze numerous communications without the physical and cognitive limitations of human sensory processing.
Solution Approach 2:
The patent creates a computational model that copies and simulates the intention inference capability of human brain-sensory systems. By training machine learning models on vast amounts of communication data, the system replicates human-like understanding of intentions while achieving greater scalability and consistency across diverse communication scenarios.
Data Source
AI summary
A method for determining an intention encoded in a given text communication, the method comprising: receiving a written text; identifying test regexes comprised in the text that are usable to indicate an intention included in the text; determining degrees of entailment of the test regexes with intention indicator regexes (IIRs) comprised in a set of IRRs; and inferring the intention based on the determined degrees of entailment.