Real-Time Virtual Corpora for Chatbot Semantic Preservation
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Solution Overview
Problem
Current distributed, interactive chatbot sessions fail to effectively preserve text and speech semantics, as chatbots lack access to a central database of learned information and repeatedly engage with users to learn information already stored by other chatbots.
Innovation Solution
The implementation of real-time virtual corpora in live interactive chatbot sessions, where chatbots perform natural language processing on user inputs, identify characteristics, and transmit inputs to a virtual corpora for analysis, allowing for the retrieval and updating of information in a global corpora based on count and ambiguity thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If chatbots operate independently with local slot memory, then each chatbot can process user inputs autonomously, but information learned by one chatbot cannot be accessed by other chatbots, leading to repeated learning and reduced efficiency
Solution Approach 1:
The patent combines multiple isolated slot memories into a unified virtual corpora that serves the entire chatbot stack. This merging allows any chatbot to access information learned by any other chatbot, eliminating redundant learning and improving overall system efficiency while maintaining autonomous processing capabilities.
Solution Approach 2:
The virtual corpora is designed as a universal information repository that serves multiple chatbots simultaneously. Instead of each chatbot having dedicated private memory, the system creates a shared resource that provides learned information to any chatbot that needs it, making the information infrastructure multi-functional and accessible across the entire system.
2Reliability
If chatbots repeatedly engage users to learn information, then each chatbot can gather comprehensive data, but the same information is learned multiple times across different chatbots, wasting time and resources
Solution Approach 1:
The system performs preliminary action by storing learned information in the virtual corpora as soon as any chatbot acquires it. This preliminary storage ensures that the information is available for immediate retrieval by other chatbots, preventing the need for repeated user engagements to learn the same information and eliminating wasted time.
Solution Approach 2:
The virtual corpora creates a feedback mechanism where information learned by one chatbot is immediately made available to others. This feedback loop prevents redundant learning by allowing chatbots to query the corpora before engaging users, ensuring information completeness while minimizing repeated user interactions.
3Loss of information
If a central global corpora is implemented, then information can be shared across all chatbots, but the complexity of managing and updating the global corpora increases significantly
Solution Approach 1:
The patent introduces the virtual corpora as an intermediary layer between individual chatbot slot memories and the global corpora. This intermediary manages the complexity of information sharing by handling storage, retrieval, and updating operations centrally, while presenting a simple interface to individual chatbots, thus reducing overall system complexity.
Solution Approach 2:
The virtual corpora is designed to be self-service, automatically managing information storage, retrieval, and updates without requiring complex external management. The system handles corpora maintenance autonomously, reducing the operational complexity that would otherwise be associated with managing a central information repository.
4Productivity
If chatbots access and update global corpora in real-time, then the system can leverage learned information across multiple interactions, but the computational overhead and processing time increase
Solution Approach 1:
The system applies local quality by allowing chatbots to access the virtual corpora selectively based on their specific information needs rather than continuously processing all available data. This targeted approach reduces computational overhead and energy consumption while maintaining real-time information retrieval efficiency for relevant queries.
Solution Approach 2:
The patent implements partial action by enabling chatbots to perform selective queries on the virtual corpora only when needed, rather than continuously accessing or updating the entire corpus. This partial engagement reduces computational energy consumption while maintaining the ability to retrieve information in real-time when necessary.
Data Source
AI summary
Aspects of the disclosure relate to preserving text and speech semantics using real-time virtual corpora in live interactive chatbot sessions. A computing platform may receive user input and may determine whether characteristics of the input are identifiable. Based on determining the characteristics are identifiable, the computing platform may populate the characteristics using a global corpora and may use the populated characteristics to generate a response to the input. Alternatively, based on determining the characteristics are unidentifiable, the computing platform may determine whether the same or a similar input is stored in a virtual corpora. If the same or a similar input is stored in the virtual corpora, the computing platform may generate a response to the input using the virtual corpora. Alternatively, if the same or a similar input was not previously received, the computing platform may gather information from the user to generate a response to the input.