Data Categorization System with Hierarchical Linking
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Solution Overview
Problem
Conventional enterprise software applications restrict users to pre-defined categories for data categorization, limiting the ability to distinguish between data elements at a granular level necessary for effective analytics and searches, and free-form tagging is discrete and not supportive of broader analytics.
Innovation Solution
An application allows users to categorize data with free-form text that can be linked to pre-defined categories, enabling more granular categorization and supporting analytics on both user-defined and pre-defined categories, thereby enhancing search and analytic capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users are restricted to pre-defined categories for data categorization, then the system structure remains simple and manageable, but the ability to distinguish between data elements at a granular level is limited
Solution Approach 1:
The patent segments the categorization system into multiple hierarchical levels (pre-defined categories, user-defined sub-categories, and custom tags). This allows data to be categorized at different granularities simultaneously, resolving the contradiction by enabling fine-grained distinction without creating a monolithic complex structure.
Solution Approach 2:
The patent implements a nested category structure where user-defined sub-categories are nested within pre-defined categories, and custom tags can be nested within sub-categories. This nesting approach allows granular categorization while maintaining a organized hierarchical structure that manages complexity through nested containment.
2Adaptability or versatility
If free-form tagging is allowed for each data element, then categorization flexibility is improved, but the tags become discrete and not supportive of broader analytics
Solution Approach 1:
The patent makes categories universal by allowing them to serve multiple functions: pre-defined categories provide broad classification for analytics, user-defined sub-categories add specificity, and custom tags provide flexible labeling. Each layer serves both specific categorization needs and broader analytic purposes, resolving the contradiction between flexibility and analytic coherence.
Solution Approach 2:
The patent merges multiple categorization approaches (pre-defined categories, user-defined sub-categories, and custom tags) into a unified hierarchical structure. This combination allows free-form flexibility at the tag level while maintaining analytic coherence through the structured hierarchy that connects all tags to broader categories.
3Measurement precision
If multiple hierarchical levels of categories are implemented, then data can be distinguished at a granular level, but the system complexity increases
Solution Approach 1:
The patent implements a dynamic category system where the hierarchy is not fixed but can be extended by users at any level. Users can create sub-categories and tags as needed, allowing the system to adapt its complexity dynamically based on actual data distinction needs rather than requiring a predetermined complex structure.
Solution Approach 2:
The patent provides pre-defined categories as a foundation before users need to create custom hierarchies. This preliminary structure reduces initial complexity and allows users to start with simple categorization, adding hierarchical levels only when and where granular distinction is actually needed.
Data Source
AI summary
A method and system including a display; a memory storing processor-executable process steps; and a processor to execute the processor-executable process steps to cause the system to: present a user interface on a display, the user interface including one or more user-entry fields to receive data categorizing an object; receive data in one or more of the displayed user-entry fields; in response to the received data, display a list of one or more pre-defined categories when the received data is not a pre-defined category; and receive a selection of the one or more pre-defined categories, linking the received data to the selected pre-defined category. Numerous other aspects are provided.