Unstructured Data Parsing for Client Ticket Aggregation

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Solution Overview

Problem

Existing methods fail to effectively parse and aggregate unstructured data objects from client tickets for analyzing root causes of issues in computer application systems, leading to inefficiencies in identifying repetitive tickets and predicting future maintenance workloads.

Innovation Solution

A computer-implemented method and system that transforms unstructured data objects by removing irrelevant words and characters, identifies criteria attributes such as word importance and sentiment, and generates reports to aggregate and predict repetitive tickets, using a processor-based system with a data retriever, transformer, criteria attributes selector, and report generator.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If unstructured data objects are manually analyzed to identify root causes of issues, then analysis accuracy may be maintained, but manual effort and time consumption increase significantly

Engineering Contradiction:

Improveticket analysis efficiencyVSAvoidtime for manual data parsing

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The patent replaces manual mechanical analysis of unstructured data with an automated computer-implemented system that uses natural language processing and machine learning algorithms to parse, transform, and aggregate ticket data, thereby eliminating manual effort while maintaining analysis capability

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables self-service automated analysis where the computer system independently performs data parsing, transformation, aggregation, and root cause identification without requiring manual intervention, allowing the system to serve itself in analyzing maintenance tickets

Inventive Principle:

Principle #25Self-service

2Reliability

If all unstructured data objects are processed in detail to ensure comprehensive analysis, then analysis completeness is improved, but processing complexity and computational resources increase

Engineering Contradiction:

Improveroot cause analysis completenessVSAvoiddata processing system complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent extracts only the relevant features and attributes from unstructured data objects using natural language processing, transforming verbose text descriptions into structured data with key attributes such as issue type, severity, and components affected, thereby reducing processing complexity while maintaining analysis completeness

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The system segments the unstructured data processing task into distinct stages: initial parsing, transformation to structured format, feature extraction, aggregation, and analysis. This segmentation allows each stage to handle specific aspects of the data, reducing overall system complexity while ensuring comprehensive processing

Inventive Principle:

Principle #1Segmentation

3Productivity

If traditional methods are used to aggregate client tickets, then data integrity is maintained, but the ability to identify patterns and predict future workloads is limited

Engineering Contradiction:

Improvemaintenance workload prediction capabilityVSAvoidpattern recognition accuracy

Core Design Contradiction:

ProductivityVSLoss of information

Solution Approach 1:

The patent transforms unstructured text data into structured parameters and attributes that can be systematically analyzed, enabling the system to identify patterns, trends, and correlations in ticket data that would be invisible in raw unstructured format, thereby improving predictive capability for future workloads

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system implements feedback mechanisms where aggregated ticket data and identified patterns are used to improve future analysis and prediction accuracy, allowing the system to learn from historical data and continuously refine its predictive models for maintenance workload forecasting

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS11144582B2Method and system for parsing and aggregating unstructured data objects

Publication Date: 2021.10.12 ACCENTURE GLOBAL SERVICES LTD

AI summary

A computer-implemented method and a system parse and aggregate unstructured data objects. The method includes obtaining the unstructured data objects from description fields of records in a database comprising client tickets that are created for application maintenance, transforming the obtained unstructured data objects to create transformed data objects, identifying a number of criteria attributes of the client tickets, where the number of criteria attributes are determined according to at least part of the transformed data objects, word importance, word sentiment, a user input, or client ticket priorities, or any combinations, and generating a plurality of ticket reports by aggregating the client tickets according to ranking orders of numbers of tickets for the client tickets and the identified criteria attributes.