Synthetic Context Objects for Ambiguous Data Retrieval
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Solution Overview
Problem
Existing databases present data in a non-dynamic, static manner, failing to provide context to ambiguous data objects, which limits their ability to accurately identify and retrieve relevant information.
Innovation Solution
The method generates and utilizes synthetic context-based objects by associating non-contextual data objects with context objects, creating meaningful synthetic context-based objects that link to specific data stores, allowing for the identification and retrieval of relevant data based on defined subject-matters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional static databases are used to store data, then data storage is simple and straightforward, but the system cannot provide context to ambiguous data objects and cannot accurately identify and retrieve relevant information
Solution Approach 1:
The patent segments data objects into two distinct types: contextual data objects (with identified subject-matter) and non-contextual data objects (without identified subject-matter). This segmentation allows the system to handle ambiguous data differently from clear data, improving retrieval accuracy by routing queries through appropriate paths while maintaining manageable complexity through clear categorization.
Solution Approach 2:
The patent introduces contextual data objects as intermediaries between non-contextual data objects and the retrieval system. When a non-contextual data object is encountered, the system creates or retrieves a corresponding contextual data object that provides the missing subject-matter context. This intermediary mechanism enables accurate retrieval without requiring complete restructuring of the entire database.
2Measurement precision
If context objects are created for every ambiguous data object to enable accurate retrieval, then data retrieval accuracy improves, but the system complexity and processing overhead increase
Solution Approach 1:
The patent implements preliminary action by pre-creating contextual data objects for commonly encountered non-contextual data objects. The system maintains a repository of contextual objects that can be quickly retrieved and associated with non-contextual objects, avoiding the need to create new contextual objects on-demand and reducing overall system complexity.
Solution Approach 2:
The patent makes contextual data objects universal by designing them to serve multiple functions: they provide subject-matter context for retrieval operations, act as intermediaries for ambiguous data, and can be reused across multiple non-contextual data objects. This multi-functionality reduces the total number of contextual objects needed and simplifies the overall system structure.
3Ease of operation
If the database associates every data object with specific data stores based on context, then data accessibility improves, but the time and resources required to maintain these associations increase
Solution Approach 1:
The patent implements self-service by enabling contextual data objects to automatically manage their own associations with data stores. When a contextual object is created or updated, the system automatically identifies and establishes appropriate associations with relevant data stores based on the object's subject-matter context, eliminating the need for manual association management and reducing maintenance time.
Solution Approach 2:
The patent incorporates feedback mechanisms where the system continuously monitors and updates contextual data object associations based on retrieval patterns and data relationships. This feedback loop allows the system to optimize associations over time, improving data accessibility while reducing maintenance overhead by only making changes when necessary based on actual usage patterns.
Data Source
AI summary
A computer-implemented method, system, and/or computer program product generates and utilizes synthetic context-based objects. One or more processors define a context object, where the context object provides a context that identifies a specific subject-matter, from multiple subject-matters, of a non-contextual data object. The processor(s) associate the non-contextual data object with the context object to define a synthetic context-based object and the synthetic context-based object with at least one specific data store. A request is received from a requester for data from said at least one specific data store that is associated with the synthetic context-based object, where said at least one specific data store is within a database of multiple data stores. Data is returned to the requester from said at least one specific data store that is associated with the synthetic context-based object.