Conversational Agent Emotion Analysis for Artwork Queries
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Solution Overview
Problem
Conventional chatbots lack the ability to effectively understand and respond to user queries about artworks and cultural exhibits, as they require extensive knowledge and emotional understanding to provide personalized and accurate information, which is challenging for real-person commentators to maintain.
Innovation Solution
An electronic conversational agent, such as a chatbot, is employed to assist users by retrieving knowledge from pre-established knowledge graphs, analyzing emotions from images, and conducting image-based interactions, allowing it to provide detailed information and answer questions about artworks, cultural relics, and other exhibits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional chatbots use keyword scanning or basic natural language processing to respond to user queries, then the response generation is simple and fast, but the chatbot cannot effectively understand and respond to queries about artworks and cultural exhibits that require extensive knowledge and emotional understanding
Solution Approach 1:
The patent introduces an electronic conversational agent as an intermediary between users and artwork information. This agent is equipped with knowledge graphs containing extensive artwork data and emotional understanding capabilities, allowing it to mediate complex queries accurately without requiring the user interface itself to be complex. The agent acts as a specialized intermediary that bridges user needs and information resources.
Solution Approach 2:
The system performs preliminary action by pre-establishing knowledge graphs with comprehensive artwork information, cultural exhibit data, and emotional understanding models before user interaction. This advance preparation of structured knowledge bases and emotional analysis frameworks enables the chatbot to provide accurate responses without requiring complex real-time processing during actual user queries.
2Reliability
If real-person commentators are used to provide personalized and accurate information about artworks, then the quality of information is high, but it is challenging to maintain consistency and availability
Solution Approach 1:
The electronic conversational agent operates autonomously to provide artwork information without requiring human commentators. It self-serves by querying pre-established knowledge graphs, analyzing user queries, and generating responses independently. This eliminates the need for human commentators while maintaining information quality and availability at all times.
Solution Approach 2:
The system creates a digital copy of expert knowledge through knowledge graphs that encapsulate comprehensive artwork information, cultural exhibit data, and emotional understanding. This digital knowledge copy replicates the expertise of human commentators, making it continuously available and consistent without human intervention while maintaining high information quality.
3Adaptability or versatility
If the chatbot provides detailed information and emotional understanding about artworks, then user engagement is enhanced, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary action by pre-processing and structuring extensive artwork information, emotional analysis frameworks, and knowledge graphs before user interaction. This advance preparation enables the chatbot to retrieve and process information efficiently during actual queries, reducing response time while maintaining detailed and emotionally intelligent responses that enhance user engagement.
Data Source
AI summary
The present disclosure provides method and apparatus for providing a response to a user in a session. At least one message associated with a first object may be received in the session, the session being between the user and an electronic conversational agent. An image representation of the first object may be obtained. Emotion information of the first object may be determined based at least on the image representation. A response may be generated based at least on the at least one message and the emotion information. The response may be provided to the user.