Open Platform Natural Language Query Mediator
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Solution Overview
Problem
Current open platforms have limited compatibility with third-party content providers for natural language queries, leading to poor user experience due to the lack of third-party providers supporting natural language queries and the inability for users to choose their preferred providers.
Innovation Solution
A data query method that transforms natural language queries into recognizable statements for third-party content providers, allowing users to select their preferred providers and sending query responses based on scheduling policies or matching degrees.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If an open platform provides only openness of data with fixed API interfaces, then data access is simplified, but compatibility with third-party content providers supporting natural language queries is poor
Solution Approach 1:
The patent introduces a natural language processing module as an intermediary component within the open platform. This module translates user natural language queries into standardized API calls that third-party content providers can understand and execute, thereby bridging the gap between simple data access interfaces and the need for natural language query support without requiring providers to implement complex NLP capabilities.
2Adaptability or versatility
If third-party content providers must support natural language queries directly, then natural language query capability is achieved, but the complexity and difficulty of integration increases significantly
Solution Approach 1:
The open platform's natural language processing module serves as a mediator that handles all NLP complexity centrally. Third-party content providers only need to implement standard data interface protocols, while the platform's NLP module translates various natural language query forms into the standardized interface calls that providers expect, thereby achieving natural language support without increasing provider integration complexity.
Solution Approach 2:
The patent creates a universal natural language processing layer within the open platform that can handle multiple types of queries and translate them into a common standardized format. This multi-functional NLP module serves all third-party content providers uniformly, allowing them to maintain simple, standardized interfaces while the platform handles the complexity of diverse natural language inputs.
3Ease of operation
If users cannot appoint their preferred third-party content providers, then system simplicity is maintained, but user experience deteriorates
Solution Approach 1:
The patent introduces dynamic user preferences and provider selection mechanisms into the open platform. Users can configure which third-party content providers they prefer for specific data types or queries, and the platform dynamically routes natural language queries to appropriate providers based on user preferences, query type, and provider capabilities, thereby enhancing user experience while maintaining system simplicity through automated routing.
Data Source
AI summary
A data query method supporting a natural language, an open platform, and a user terminal are provided, where the method includes: receiving, by the open platform, a natural language query statement sent by the user terminal, and transforming the natural language query statement into a query statement that is recognizable by a third-party content provider; sending, by the open platform, the query statement that is recognizable to one or more third-party content providers; receiving, by the open platform, one or more query response messages returned by the one or more third-party content providers according to the query statement that is recognizable; and sending, by the open platform, the one or more query response messages to the user terminal.