Neural Network Vectorization for Unanswered Query Detection
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Solution Overview
Problem
Existing systems struggle to identify and address unanswered portions of customer queries in application resolution reports, leading to unresolved issues and additional communication needs.
Innovation Solution
A method involving the application of a neural network algorithm to vectorize application resolution reports, perform probability analysis to detect unanswered portions, and initiate query resolution accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If traditional text analysis methods are used to review application resolution reports, then manual review capability is maintained, but the system cannot automatically identify unanswered query portions
Solution Approach 1:
The patent replaces manual text analysis with a neural network-based natural language processing system. The neural network algorithm processes application resolution reports to automatically identify unanswered query portions, substituting human mechanical review with automated intelligent analysis.
Solution Approach 2:
The patent introduces a neural network algorithm as an intermediary between the application resolution report and the identification of unanswered queries. This intermediary processes the text through vectorization and probability analysis to detect responses that do not adequately address customer queries.
2Reliability
If comprehensive query analysis is performed to ensure all customer questions are answered, then query resolution completeness improves, but additional communication with customers may be required
Solution Approach 1:
The patent performs preliminary analysis of application resolution reports to identify unanswered query portions before additional customer communication is initiated. By detecting incomplete responses in advance, the system allows support personnel to address missing information proactively, reducing the need for back-and-forth communication cycles.
Solution Approach 2:
The patent implements a feedback mechanism where the neural network analyzes resolution reports and provides information about unanswered queries back to the support process. This feedback loop enables continuous improvement of query resolution completeness by highlighting specific portions that require attention.
3Measurement precision
If manual review of application resolution reports is conducted, then detailed analysis is possible, but processing efficiency and speed decrease
Solution Approach 1:
The patent replaces manual text analysis with automated neural network processing. The system vectorizes text inputs and applies probability analysis through the neural network to identify unanswered queries, achieving both high accuracy in detection and rapid processing of multiple reports simultaneously.
Solution Approach 2:
The patent transforms text data into vector representations, changing the parameter space from human-readable text to numerical vectors that the neural network can process efficiently. This parameter transformation enables fast mathematical operations while preserving the semantic meaning necessary for accurate analysis.
Data Source
AI summary
A method for managing applications includes obtaining an application resolution report from an administrative system, wherein the application resolution report comprises a customer query and a response, applying a neural network algorithm on a set of tokens associated with the application resolution report to obtain a vector representation of the application resolution report, performing a probability analysis on each vector in the vector representation, based on the probability analysis, identifying an unanswered portion of the application resolution report, and in response to the unanswered portion of the application resolution report, performing a query resolution.