Semantic Query Consolidation for Accurate Application Routing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems face challenges in determining which application can perform a specific action on a given entity efficiently, accurately, and reliably, especially in voice-based computing environments where applications store data in different databases and do not semantically specify their functions or inventories.
Innovation Solution
A data processing system combines structured and unstructured data feeds, uses knowledge graphs, and natural language processing to match user queries with applications capable of performing the desired actions on identified entities, ensuring only compatible applications are executed, thereby reducing unnecessary resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system queries multiple databases to obtain requested information, then the information retrieval capability is improved, but the system complexity and processing time increase
Solution Approach 1:
The patent introduces an intermediary component that acts as a mediator between the user's information request and the multiple databases. This intermediary consolidates the queries, manages the data retrieval process across disparate sources, and integrates the results, thereby improving information retrieval capability while abstracting away the complexity of interacting with multiple databases directly.
Solution Approach 2:
The patent merges multiple database queries and data sources into a unified response mechanism. By combining the retrieval operations and consolidating the results from disparate databases, the system achieves comprehensive information retrieval while reducing the apparent complexity for the user and application.
2Adaptability or versatility
If the system routes requests to numerous databases or servers, then the data source coverage is improved, but the processing time and resource utilization increase
Solution Approach 1:
The patent implements preliminary action by pre-consolidating query routes and data source mappings. The system prepares and optimizes the query distribution strategy in advance, so when a request arrives, the routing to numerous databases can be executed efficiently without ad-hoc decision-making, thereby maintaining broad data source coverage while reducing processing time.
Solution Approach 2:
The patent utilizes parameter changes by dynamically adjusting query timing, data retrieval priorities, and processing sequences based on the specific request and available data sources. This allows the system to optimize processing time for each query while still accessing the necessary diverse data sources, effectively changing operational parameters to balance coverage and speed.
3Adaptability or versatility
If applications store data in different databases without semantic specification, then the data storage flexibility is improved, but the data integration and query accuracy deteriorate
Solution Approach 1:
The patent implements a universal data access layer that can interface with multiple different database types and storage formats. This universal interface maintains the flexibility of storing data in various databases while providing standardized access methods that improve query accuracy by consistently interpreting and retrieving data regardless of the underlying storage format.
Solution Approach 2:
The patent replaces direct mechanical querying of disparate databases with an intelligent data access system that uses semantic understanding and data mapping. This substitution allows the system to maintain flexible data storage across different databases while achieving accurate queries through semantic layering that translates user requests into appropriate database-specific queries.
Data Source
AI summary
Consolidation of disparate data source queries is provided. An application intake component can receive an application package file, and process the file to identify one or more actions and entities for the application. A natural language processor component can receive an input audio signal to identify an action and an entity on which to perform the action. An application delivery component can identify applications that can perform the action and applications that have access to the entity, and then select an application that is configured to perform the action on the entity. The application delivery component can provide an indication of the application selected by the system to a client device.