Object Type Selection Using Ontology Ranking and AI Relevance
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Solution Overview
Problem
Conventional systems lack efficient tools for managing complex object models, leading to slow loading times, incorrect object type selection, and inconsistent output in software application building, particularly in low-code and no-code environments.
Innovation Solution
An object type management system utilizing an object type selector that employs relevancy algorithms, AI models, and ontology search tools to rank and present object types based on relevance, use history, and policy, allowing faster and more accurate selection of object types for software application building.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional systems are used for managing object models, then device complexity is reduced, but productivity decreases due to slow loading times and inefficient object type selection
Solution Approach 1:
The patent introduces an object type selector as an intermediary component between the user and the object model. This selector uses relevancy algorithms and AI models to automatically rank and filter object types based on search queries, use history, and policy, thereby improving selection efficiency without requiring users to manually navigate complex object models.
Solution Approach 2:
The system performs self-service by automatically ranking and filtering object types based on relevancy algorithms, AI models, and predefined policies. The object type selector autonomously processes search queries, uses historical data, and applies business rules to determine the most relevant object types, reducing the manual effort required from users.
2Adaptability or versatility
If comprehensive object models are used, then adaptability improves, but speed decreases due to slow loading times
Solution Approach 1:
The system performs preliminary action by pre-ranking and pre-filtering object types based on relevancy algorithms, AI models, and policy before the user actually needs to select one. The object type selector continuously maintains ranked lists of object types, so when a search query is received, the system can quickly present already-organized information rather than loading and sorting everything from scratch.
Solution Approach 2:
The patent segments the object model into manageable groups and categories, with the object type selector processing different segments independently. By dividing the comprehensive object model into organized structures that can be selectively loaded and ranked, the system maintains adaptability while improving loading speed through parallel processing of segments.
3Measurement precision
If manual object type selection is used, then device complexity is reduced, but measurement precision decreases due to incorrect object type selection
Solution Approach 1:
The object type selector incorporates feedback mechanisms by analyzing use history and adjusting rankings accordingly. The system learns from user interactions and feedback to improve its selection accuracy over time, using relevancy algorithms that incorporate historical data and policy information to refine future object type recommendations.
Solution Approach 2:
The patent replaces manual mechanical selection processes with automated AI-based systems. Instead of relying on users to manually search and select object types, the system uses AI models and relevancy algorithms to automatically determine the most appropriate object types, thereby improving selection accuracy while managing complexity through automation rather than user effort.
Data Source
AI summary
In some examples, systems and methods for selecting object types and/or managing object models are provided. For example, a method includes: receiving a search query related to a use case; searching one or more ontologies based on the search query to generate a list of object types, the list of object types including one or more object type groups, each object type group of the one or more object type groups including a set of pre-selected object types; ranking the list of object types based on one or more ranking criteria; generating a presentation representing the list of object types based at least in part on the ranking; and causing a display of the presentation representing the list of object types.