Knowledge Graph Custom Report Builder
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Solution Overview
Problem
Conventional systems for defining custom reports lack guidance to ensure consistency with domain semantics, leading to potential errors and user frustration, and often require users to work within predefined templates, limiting customization options.
Innovation Solution
A method and system that utilize a knowledge graph to dynamically guide user actions through a graphical user interface, allowing users to select entities and attributes based on selectability conditions, thereby refining the report schema to be consistent with the domain semantics without requiring code writing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional systems allow users to define custom reports without guidance, then users have freedom in report customization, but report accuracy and consistency with domain semantics deteriorates
Solution Approach 1:
The system provides real-time feedback to users during report definition by validating selections against domain rules. When users make selections that would violate accounting principles or domain semantics, the system immediately notifies them, allowing correction before report generation. This feedback mechanism maintains both user freedom and report accuracy.
Solution Approach 2:
The system performs preliminary validation of report definitions against domain rules before allowing report generation. By checking selections against predefined domain semantics in advance, the system prevents erroneous reports from being generated while maintaining user customization freedom.
2Device complexity
If conventional systems provide error notifications after report definition, then system complexity is reduced, but user experience and time to resolve errors deteriorates
Solution Approach 1:
The system performs validation checks during the report definition process itself, before reaching the error notification stage. By conducting preliminary validation at the point of selection, the system eliminates the need for subsequent error notifications and resolution cycles, reducing both time loss and system complexity.
Solution Approach 2:
The system implements real-time feedback mechanisms that provide immediate guidance when users make selections that may lead to errors. This continuous feedback during the definition process eliminates the need for post-definition error notifications, reducing time to resolve issues while maintaining simple system architecture.
3Reliability
If conventional systems require predefined templates for custom reports, then report generation reliability is improved, but user customization capability deteriorates
Solution Approach 1:
The system dynamically adapts the set of available report elements and validation rules based on the user's selections and the domain context. Rather than requiring users to work within fixed templates, the system dynamically generates appropriate options and constraints, maintaining reliability through domain-aware validation while enabling extensive customization.
Solution Approach 2:
The system changes the parameters of report definition dynamically based on user selections and domain context. By adjusting the available options, validation rules, and guidance information in real-time, the system maintains report generation reliability while providing flexible customization capabilities that go beyond predefined templates.
Data Source
AI summary
A method may include obtaining a knowledge graph including entities, and determining, for the knowledge graph, a first state including a first selectable entity subset of the entities that are selectable by a user. The first selectable entity subset may include an entity. The method may further include receiving, from the user and via a graphical user interface (GUI), a selection of the entity from the first selectable entity subset, and responsive to the selection, adding the entity to a report schema. The report schema may be used to populate a report. The method may further include, responsive to the selection, transitioning the knowledge graph to a second state including a second selectable entity subset of the entities that are selectable by the user.