Entity Knowledge Database for AI Model Selection
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Solution Overview
Problem
As the number of recognition models available on AI platforms increases, users face difficulty in determining which models are available and suitable for recognizing specific objects in a data set, making it challenging to efficiently identify objects within the data.
Innovation Solution
An AI system utilizing an entity knowledge database, such as a graph database, to link recognition models with entities, allowing for the automatic selection of appropriate models based on queries, and processing data sets using these selected models to indicate the presence of objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple recognition models are made available on AI platforms, then the capability and accuracy of object recognition is improved, but the complexity of determining which models are available and suitable for specific objects increases
Solution Approach 1:
The patent introduces an entity knowledge database as an intermediary system that mediates between the user's object identification needs and the available recognition models. The database stores ontological relationships between entities and models, automatically resolving the complexity of model selection by providing a structured knowledge base that maps objects to suitable models without requiring users to manually evaluate multiple models.
Solution Approach 2:
The system implements feedback mechanisms where the entity knowledge database provides continuous information about model capabilities and ontological relationships. This feedback loop enables the system to automatically select appropriate models based on the queried objects, reducing the cognitive load on users while maintaining high recognition accuracy through informed model selection.
2Ease of operation
If an entity knowledge database is introduced to manage recognition models, then the ease of determining suitable models is improved, but the device complexity increases
Solution Approach 1:
The entity knowledge database serves multiple functions simultaneously: it stores ontological relationships, provides model metadata, enables automatic model selection, and facilitates resource compatibility assessment. By making the knowledge base multi-functional, the patent reduces the need for separate systems while maintaining ease of operation, as a single database structure handles diverse tasks related to model management.
Solution Approach 2:
The patent embeds multiple levels of information within the entity knowledge database structure, organizing models, entities, and their relationships in a nested hierarchical manner. This nesting allows the system to manage complexity internally while presenting a simple interface externally, as the nested structure enables automatic traversal and selection without exposing the underlying complexity to users.
3Adaptability or versatility
If recognition models are linked to multiple entities in the knowledge database, then the adaptability of the system is improved, but the difficulty of selecting appropriate models increases
Solution Approach 1:
The patent segments the entity knowledge database into distinct ontological levels and relationship types, organizing the complex mappings between models and entities in a structured, hierarchical manner. This segmentation allows the system to handle multiple linkages systematically, breaking down the complexity of model selection into manageable queries that traverse specific ontological levels rather than facing a flat, unstructured mapping problem.
Data Source
AI summary
An artificial intelligence device for identifying an object in a data set includes processing circuitry configured to receive the data set and a query including object. The processing circuitry selects one or more models using an entity knowledge database that includes a plurality of entities corresponding to objects to be identified. Each of a plurality or recognition models is linked to multiple entities of the entity knowledge database so that the processing circuitry may select multiple recognition models. The processing circuitry then processes the data set using the selected recognition model or models to provide an indication of whether the data set includes the at least one object. The entities may be ontologically coupled in the database so that, even if the object does not have a corresponding entity in the database, the object may be identified using models selected based on the ontology.