Score Feedback System for Requirement Matching
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems for matching user requirements with complementary services, jobs, or products do not provide adequate feedback on rejection causes, limiting users' ability to enhance their chances of achieving their goals.
Innovation Solution
A method and system that extract internal and external parameters from user data objects, compare them with competing and complementary users, compute scores indicating the likelihood of requirement fulfillment, and provide feedback to enhance these scores by modifying parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If manual or machine learning algorithms are used to match user requirements with complementary services, then matching functionality is achieved, but users lack information about rejection causes and cannot enhance their chances
Solution Approach 1:
The system implements feedback by computing and providing scores to users that indicate their likelihood of achieving requirements. The system analyzes multiple parameters including user attributes, service attributes, and historical data to generate feedback scores that inform users about their matching status and areas for improvement, thereby resolving the information loss about rejection causes.
Solution Approach 2:
The system performs preliminary analysis of user requirements and complementary services before final matching occurs. By pre-computing scores based on extracted parameters and comparing them against thresholds, the system prepares matching recommendations in advance, enabling users to understand potential outcomes before committing to a match.
2Ease of operation
If users are rejected without feedback, then processing speed is maintained, but user ability to improve matching success is limited
Solution Approach 1:
The system applies partial action by computing scores selectively based on the most relevant parameters rather than analyzing all possible factors. It extracts key parameters from user and service data objects and focuses computation on comparing these essential elements, providing sufficient feedback without requiring exhaustive analysis of every possible attribute.
Solution Approach 2:
The system utilizes parameter changes by dynamically adjusting score computations based on extracted parameters from data objects. It transforms raw user and service attributes into standardized parameters that can be compared and scored, enabling efficient evaluation while maintaining comprehensive assessment capability.
3Measurement precision
If comprehensive parameter extraction and comparison is performed, then matching accuracy is improved, but computational complexity increases
Solution Approach 1:
The system segments the matching process into distinct stages: extracting parameters from data objects, comparing parameters between user requirements and complementary services, computing scores based on parameter comparisons, and providing feedback. This segmentation allows each stage to be optimized independently, improving overall accuracy while managing computational complexity through modular processing.
Data Source
AI summary
Methods, systems and computer program products are provided for computing relative score and enhancing one or more scores associated with data objects. In one method, the method receives, at a computing system, one or more data objects from a user. The method further extracts one or more internal and external parameters based on the one or more data objects. Subsequently, the method compares data objects of the user with corresponding data objects of one or more competing users, based at least in part on the one or more extracted parameters and the requirement included in the data object of the user. Further, in some embodiments, the data objects and requirements of the user are also compared with the corresponding data objects and requirements of one or more complementary users, based at least in part on the one or more extracted parameters. The method further computes one or more scores associated with the data objects based at least in part on the at least one of the comparison of the one or more data objects of the user with the corresponding data objects of one or more competing users and/or the one or more extracted parameters. The method may also provide feedback to the user, where the feedback is directed to enhance the one or more computed scores associated with the data objects.