Service Information Entry Prompts for Accurate Recommendation Data
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Solution Overview
Problem
Existing service information entry systems rely on manual input by service providers, leading to inaccurate or poor quality of service information, which affects the effectiveness of recommended content items.
Innovation Solution
A method and apparatus that utilize a machine learning model to generate entry prompts for a service information entry interface, based on feature information and service recommendation data, to guide service providers in entering more accurate and efficient service information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual input by service providers is used for service information entry, then the system operation is simple, but the quality and accuracy of service information deteriorates
Solution Approach 1:
The patent introduces an automated information extraction system that acts as an intermediary between service providers and the recommendation system. This intermediary automatically extracts service information from various sources (webpages, documents, images) and fills the service information entry interface, eliminating the need for manual input while ensuring high information quality and accuracy.
Solution Approach 2:
The system enables self-service by allowing service information to be automatically extracted and populated without requiring service provider intervention. The automated extraction system processes information sources and fills entry fields autonomously, improving information quality while reducing operational complexity.
2Manufacturing precision
If automated information extraction is implemented, then the quality of service information improves, but the device complexity increases
Solution Approach 1:
The patent implements a universal information extraction system that handles multiple information sources (webpages, documents, images) and multiple entry item types through a single integrated platform. This multi-functional approach improves information quality across all service types while managing system complexity through consolidation rather than proliferation of separate systems.
Solution Approach 2:
The system dynamically adjusts extraction parameters and processing methods based on the type of information source and entry items. By changing parameters adaptively rather than using fixed complex structures, the system maintains high information quality while managing complexity through flexible configuration.
3Productivity
If manual entry interface is used, then the device complexity is low, but the productivity of service information entry deteriorates
Solution Approach 1:
The system performs preliminary actions by automatically extracting and preparing service information before the service provider needs to enter it. Information is pre-processed, validated, and populated into the entry interface in advance, dramatically improving entry efficiency while the complexity is managed through automated workflows.
Solution Approach 2:
The patent replaces the mechanical manual entry process with an automated information extraction and population system. This substitution eliminates manual typing and copying operations, improving productivity significantly while the system complexity is managed through software automation rather than physical processes.
Data Source
AI summary
According to embodiments of the disclosure, a method, an apparatus, a device and a medium for information interaction are provided. The method includes: in response to detecting an information entry request for a target service, presenting a service information entry interface corresponding to the target service, where the service information entry interface includes a plurality of entry items respectively corresponding to a plurality of types of service information; obtaining at least one entry prompt respectively associated with at least one of the plurality of entry items, where the at least one entry prompt is determined by using a machine learning model based on at least one of: feature information associated with the target service, and service recommendation information corresponding to a service type to which the target service belongs; and presenting the at least one entry prompt in association with the at least one entry item.