Chatbot Information Processing via Universal Data Model
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Solution Overview
Problem
Users face complexity and repetitive tasks when interacting with multiple chatbots across different domains, leading to a poor user experience due to the need to provide similar information multiple times.
Innovation Solution
A computer-implemented method that retrieves chat information, determines a matching data model based on the chat context, and extracts data values to generate responses, allowing for seamless interaction across various chatbots without requiring explicit changes to the chatbot implementation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple chatbots are used for different industry domains, then the functionality and versatility of the system is improved, but the interface complexity and user burden increase
Solution Approach 1:
The patent implements a universal data model framework that enables multiple chatbots across different industry domains to share common data structures and interfaces. The data model acts as a universal layer that accommodates various domains (finance, healthcare, e-commerce, etc.) while maintaining consistent interaction patterns for users, thus achieving multi-functionality without proportionally increasing interface complexity
Solution Approach 2:
The patent segments the chatbot system into distinct modular components: domain-specific chatbot modules, a universal data model layer, and a common processing framework. This segmentation allows each chatbot to be developed independently for its specific domain while sharing the underlying data model and infrastructure, reducing overall system complexity through modularity
2Adaptability or versatility
If multiple chatbots are used for different industry domains, then the functionality and versatility of the system is improved, but the repetitive input requirements increase
Solution Approach 1:
The patent implements preliminary action by pre-defining standardized data models and data objects that capture common information structures across different domains. These data models are prepared in advance with predefined schemas, allowing the system to automatically map and reuse user-provided information across multiple chatbot interactions without requiring users to re-enter the same data repeatedly
Solution Approach 2:
The patent enables copying of user information and context across different chatbot sessions by maintaining a unified data model representation. When a user provides information to one chatbot, the system copies and stores this information in the standardized data model format, making it automatically available for subsequent interactions with other chatbots in the same or different domains, eliminating repetitive input
3Productivity
If data models are shared across chatbots, then the efficiency and consistency of interactions are improved, but the complexity of data model management increases
Solution Approach 1:
The patent segments data models into hierarchical layers: core universal data models that apply across all domains, and domain-specific extensions that build upon the core models. This segmentation allows the system to manage complexity by handling only the essential universal models at the foundation level while allowing domain-specific variations without requiring management of entirely separate data models for each domain
4Ease of manufacture
If existing chatbot logic is preserved without alteration, then the implementation cost and disruption are reduced, but the ability to share context and data models is limited
Solution Approach 1:
The patent introduces an intermediary data model layer that sits between existing chatbot logic and the context-sharing infrastructure. This intermediary layer translates and standardizes data from various chatbot sources into a unified format, enabling context sharing and data model integration without requiring modifications to the existing chatbot implementations. The intermediary acts as an adapter that preserves legacy systems while enabling new capabilities
Data Source
AI summary
A computer-implemented method, a computer system, and a computer program product are proposed. According to the method, chat information of a chatbot is obtained in response to receiving one or more chat messages from the chatbot. Then a matching data object of a matching data model from one or more data models is determined based on the chat information. And a data value of the matching data object is obtained as a response to the one or more chat messages.