Navigation Path Analysis for Software Assistance
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Solution Overview
Problem
Users face challenges in navigating computer software and physical spaces due to the high volume of ticket generation for navigation assistance, especially when encountering failures or system instability, which diverts developer resources from higher priority tasks.
Innovation Solution
A method and system that utilize machine logic to analyze historical navigation paths, creating a weighted directed graph to determine favorable navigation paths, reducing manual effort and ticket generation by providing alternative paths based on successful user journeys, and using unsupervised and supervised machine learning to cluster and assess navigation steps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional navigation assistance is provided through front-end interfaces and help content, then users receive navigation support, but high volume of ticket generation occurs when users encounter failures or system instability
Solution Approach 1:
The system enables self-service navigation assistance by automatically monitoring user navigation paths, comparing them against a knowledge base of successful paths, and providing real-time guidance without requiring developer intervention. The system serves itself by using collected navigation data to continuously improve its guidance capabilities, reducing the need for external support resources.
Solution Approach 2:
The system implements feedback mechanisms by monitoring user navigation paths, comparing them with known successful paths, and providing real-time feedback when users deviate from optimal navigation routes. This feedback loop allows the system to adapt and improve navigation assistance based on actual user behavior patterns.
2Ease of operation
If navigation paths are monitored and analyzed to provide assistance, then user experience is improved, but system complexity increases due to data collection and analysis requirements
Solution Approach 1:
The system creates simplified copies of successful navigation paths by monitoring and recording user navigation sequences. Instead of implementing complex real-time analysis of all possible navigation scenarios, the system captures representative navigation patterns and uses these copies as templates for providing guidance, thereby reducing system complexity while maintaining effectiveness.
3Productivity
If alternative navigation paths are provided based on successful user journeys, then ticket generation is reduced, but time is required to collect and process navigation data
Solution Approach 1:
The system performs preliminary actions by proactively monitoring and collecting navigation path data during normal system operation. Rather than waiting for failures to occur and then analyzing data, the system continuously builds a knowledge base of successful navigation paths in advance, so that when users do encounter issues, guidance can be provided immediately using pre-processed information.
Data Source
AI summary
When human users traverse physical space or traverse computer software, they take “navigational paths.” Some embodiments of the present invention are directed to machine logic for identifying a favorable navigation paths by monitoring physical or computer software navigation paths used by human users as they use a set of computer program(s). This favorable navigation path, through physical space or the logic of the set of computer program(s), can then be suggested to future users who want to navigate from a similar starting point to a similar end point.