Category-Based Review Suggestion for Richer Product Comments
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Solution Overview
Problem
Existing commodity comment systems suffer from low-quality user-generated content due to limited expression capabilities and mechanical, stereotyped comments, making it difficult for users to provide effective references for others.
Innovation Solution
An AI-driven method analyzes user comment content by commodity category to determine decision-making factor labels, processes basic comment content to generate suggested text content, and optimizes picture/video content, enhancing the completeness and relevance of user comments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If users are provided with reference labels to structure comment content, then the completeness of comment content is improved, but the comments become mechanical and stereotyped
Solution Approach 1:
The system dynamically adjusts comment generation by combining structured reference labels with user's free-text input. The AI model processes both the selected labels and the user's own words to generate comments that maintain structure while preserving natural expression variations, preventing mechanical repetition.
Solution Approach 2:
An AI language model acts as an intermediary between the structured reference labels and the final comment output. The AI processes the labels along with the user's basic input to generate natural-sounding comments, mediating between the rigid structure of labels and the need for expressive freedom.
2Loss of information
If users spend more time contemplating how to express comments, then the quality of comment content is improved, but the time cost increases
Solution Approach 1:
The system performs preliminary processing by pre-defining reference labels based on commodity categories and analyzing existing high-quality comments. When users submit comments, the AI model is already prepared with relevant labels and can quickly generate quality suggestions without requiring users to spend extensive time contemplating expression.
Solution Approach 2:
The AI model automatically generates suggested comment content by processing the user's basic input and the relevant reference labels. This self-service capability provides quality comment suggestions without requiring users to invest significant time in contemplation, as the system handles the complex generation task autonomously.
3Loss of information
If users provide detailed comment content, then the reference value for other users is improved, but the effort required from users increases
Solution Approach 1:
The system adopts a partial action approach where users only need to provide basic comment content and select reference labels, rather than writing complete detailed comments themselves. The AI model completes the rest by generating suggested comment content that incorporates both the user's input and the structured labels, achieving detailed output with minimal user effort.
Solution Approach 2:
The AI language model serves as an intermediary that transforms the user's brief input and selected labels into detailed comment content. This intermediary handles the complex task of expanding and elaborating on user input, providing detailed reference-value comments without requiring users to invest significant writing effort.
Data Source
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AI summary
Embodiments of this application disclose a method for processing commodity comment content and an electronic device. The method includes: analyzing, by using a commodity category as a unit, user comment content corresponding to a plurality of commodities, to determine a correspondence between a commodity category and a decision-making factor label; obtaining, after a target user initiates a request for filling user comment content for a target commodity object, basic comment content inputted by the target user; and processing the basic comment content according to the decision-making factor label corresponding to a commodity category to which the target commodity belongs, to generate suggested comment text content, so as to publish user comment content for the target commodity according to the suggested comment text content. According to the embodiments of this application, quality of user comment content of a commodity in a system can be improved.