Messenger App Information Processing for Approval Requests
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Solution Overview
Problem
In existing business chat systems, it is challenging to create application information necessary for approval when item information is insufficiently obtained from applicant posts, often requiring default values or preset options, which can lead to incomplete or inaccurate data.
Innovation Solution
An information processing apparatus that compensates for missing item information by referencing the conversation history within the messenger app, allowing for the creation of application information without directly inquiring the applicant, using natural language processing to extract relevant details from previous messages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If default values or preset options are used to compensate for missing item information, then the application process can proceed without additional user input, but the accuracy and completeness of the application information deteriorates
Solution Approach 1:
The system performs preliminary analysis of conversation history before application submission to extract and store relevant item information. By proactively gathering data from past communications between applicant and approver, the system prepares accurate information in advance, eliminating the need to use default values and ensuring completeness without additional user input.
Solution Approach 2:
The system analyzes feedback from conversation history between applicant and approver to identify and extract relevant item information. By monitoring and processing communicative exchanges, the system captures contextual data that would otherwise be missing, improving accuracy while maintaining ease of operation.
2Measurement precision
If conversation history is analyzed to extract missing item information, then the accuracy and completeness of application information improves, but the processing time and system complexity increases
Solution Approach 1:
The system extracts only the specific item information needed for the application from the broader conversation history, rather than processing entire communication transcripts. By selectively identifying and extracting relevant data points related to application items, the system improves completeness while minimizing processing complexity and time.
Solution Approach 2:
The system implements a multi-functional processing mechanism that handles both conversation analysis and application information compilation through a unified approach. By integrating these functions, the system reduces overall complexity despite performing sophisticated information extraction from historical communications.
3Ease of operation
If conversation history is referenced to compensate for missing information, then additional user input is avoided, but the risk of using incorrect or outdated information increases
Solution Approach 1:
The system dynamically evaluates conversation history context to determine the most current and relevant item information, rather than relying on static or outdated data. By adapting to the temporal and contextual nature of communications, the system ensures reliability while minimizing the need for additional user input.
Solution Approach 2:
The system uses feedback from the content and context of conversations between applicant and approver to verify and validate extracted item information. By analyzing the communicative exchange patterns, the system ensures that extracted data is accurate and current, maintaining reliability without requiring additional user confirmation.
Data Source
AI summary
An information processing apparatus includes a processor configured to, to create application information that is necessary to obtain approval in response to a post from an applicant to a messenger app for requesting an application, if item information to be included in the application information is not obtained from the post from the applicant to the messenger app, compensate for the item information by referring to a history of conversation with the applicant using the messenger app.