Intent-Based Report Templates for Faster Report Creation
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Solution Overview
Problem
Current reporting applications require users to manually select numerous fields and filters for report creation, leading to complexity and frustration, and lack the ability to assist users in creating similar reports based on past selections.
Innovation Solution
A system and method that uses machine learning and natural language processing to identify user intent from past reports, generating prepopulated report templates with common features and filters, reducing the need for manual selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If users manually select numerous fields and filters for report creation, then report customization and precision are improved, but user effort and complexity increase
Solution Approach 1:
The system performs preliminary action by pre-selecting fields and filters based on analyzed user intent before the user needs to create a report. The intent analysis module examines historical reports and user behavior to determine what fields and filters should be pre-selected, eliminating the need for users to manually navigate and select from numerous options while maintaining report precision and customization.
2Adaptability or versatility
If reporting applications provide comprehensive field selection, then report versatility is improved, but device complexity increases
Solution Approach 1:
The reporting application performs self-service through automated intent analysis that examines historical reports and user behavior patterns. The system automatically determines which fields and filters should be selected based on the analyzed intent, eliminating the need for complex manual navigation interfaces while maintaining comprehensive field selection capabilities and report versatility.
3Manufacturing precision
If users create reports from scratch each time, then report customization is improved, but time consumption increases
Solution Approach 1:
The system performs preliminary action by analyzing historical reports and pre-configuring field selections based on determined user intent before the user needs to create a new report. This eliminates the need for users to start from scratch each time while maintaining customization, significantly reducing report creation time.
4Measurement precision
If the system logs user steps, then tracking accuracy is improved, but information usefulness decreases
Solution Approach 1:
The system performs self-service by automatically analyzing logged user steps to determine intent and generate recommendations without requiring users to manually provide additional information. The intent analysis module processes the logged data to identify patterns and generate useful recommendations for future reports, transforming raw logs into actionable insights.
Data Source
AI summary
The present disclosure relates generally to tools to determine a user's intent and, more particularly, to a system, method and computer program product to generate a report template based on user's intent. The method includes: extracting, by a computer system, text and user selected features from one or more reports built in a reporting application; classifying, by the computer system, keywords in the text and the select features; identifying, by the computer system, common keywords and associated selected features within the one or more reports; determining, by the computer system, an intent of the user based on the common keywords and associated selected features; and generating, by the computer system, a report template with prepopulated features of the selected features based on the intent of the user.