Chatbot Event Subscription via Semantic Engine and Mediator Server
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing chatbots lack the ability to react to user wishes expressed previously, as they do not retain knowledge of past interactions and cannot process future concepts, leading to transient exchanges and inability to alert users about asynchronous events.
Innovation Solution
A method and device that utilize a semantic engine to interpret user requests, determine the relevant event server, and send asynchronous notifications in natural language when the event occurs, allowing users to subscribe to events such as TV programs, stock prices, or weather alerts, with the option to delegate event monitoring to specialized servers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a chatbot uses simple immediate interaction, then the interaction is easy to implement, but the chatbot cannot react to user wishes expressed previously or process future concepts
Solution Approach 1:
The patent introduces an event server as an intermediary component between the chatbot and event sources. The event server handles event monitoring and management, allowing the chatbot to focus on natural language processing and user interaction. This mediator enables the chatbot to react to user wishes about future events without the complexity of implementing event monitoring directly in the bot's code.
Solution Approach 2:
The system performs preliminary actions by having users express their wishes in advance through natural language. The chatbot interprets these wishes using a semantic engine and sets up event subscriptions before the events occur. This allows the system to prepare and react to future events rather than only responding to immediate queries.
2Adaptability or versatility
If a chatbot monitors all possible events, then the chatbot can respond to any user request, but the coding complexity becomes too high
Solution Approach 1:
The patent segments the system into distinct components: the chatbot for natural language processing, the semantic engine for interpreting user intent, and specialized event servers for monitoring specific event types. This segmentation allows each component to handle specific tasks efficiently, enabling broad event coverage without concentrating all complexity in a single chatbot system.
Solution Approach 2:
The event server is designed as a universal component that can handle multiple types of events through a standardized interface. Rather than creating specialized monitoring code for each event type within the chatbot, the universal event server provides multi-functional event monitoring capabilities that serve various user requests.
3Ease of operation
If a chatbot processes natural language requests, then user interaction is easy, but the chatbot cannot retain knowledge of past interactions
Solution Approach 1:
The system implements feedback by continuously monitoring events and sending notifications back to users when their previously expressed wishes are fulfilled. The event server tracks event states and provides feedback to the chatbot, which then communicates with users about the status of their requests, creating a closed-loop information flow that retains knowledge of past interactions.
Data Source
AI summary
A method is proposed for alerting that an event has occurred. The method comprises: receiving a user request; interpreting the user request using a semantic engine and determining a request to subscribe to an event contained in the request; determining an event server on the basis of the event; sending to the event server a request to subscribe to the event; receiving a first message associated with an occurrence of the event; sending a second message informing of the occurrence of the event.