Iterative Search Result Prioritization Using Dynamic Adjustment Values
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Solution Overview
Problem
Conventional information storage and retrieval systems fail to provide accurate search results due to the use of approximate values for object properties, leading to mismatches even when the properties of real objects are the same, as these systems cannot find matches among entries with different approximate values.
Innovation Solution
A method that iteratively modifies and prioritizes search terms by associating priority adjustment values, performing a series of fuzzy searches, and calculating a priority adjustment sum to generate and prioritize search results, ensuring that results closer to the original search terms are ranked higher.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional information storage and retrieval systems use approximate values for object properties, then storage flexibility is improved, but search accuracy deteriorates because entries with different approximate values cannot be matched even when the properties of real objects are the same
Solution Approach 1:
The system dynamically adjusts search parameters by performing multiple iterations with different priority adjustment values. Instead of using a static search approach, the system adapts by modifying search terms and priority values across iterations, allowing it to handle approximate values effectively while maintaining search accuracy through iterative refinement.
Solution Approach 2:
The system changes parameters by associating different priority adjustment values with search terms across multiple iterations. By modifying priority adjustment values and re-executing searches with adjusted parameters, the system can retrieve entries with approximate values while maintaining accuracy through parameter variation and iterative optimization.
2Measurement precision
If multiple search iterations are performed with priority adjustment values, then search accuracy is improved, but processing time increases
Solution Approach 1:
The system performs a limited number of iterations (MAX iterations) rather than exhaustive searching. By setting a reasonable iteration limit and using priority adjustment values to guide the search, the system achieves sufficient accuracy without excessive processing time, balancing thoroughness with efficiency.
Solution Approach 2:
The system performs preliminary actions by pre-calculating priority adjustment values and organizing search terms before executing the full search process. This preliminary organization allows subsequent iterations to proceed more efficiently, reducing overall processing time while maintaining accuracy.
3Measurement precision
If priority adjustment values are associated with each search term, then result prioritization is improved, but system complexity increases
Solution Approach 1:
The system segments the search process into distinct components: search terms, priority adjustment values, and iterations. By dividing the complex search operation into manageable segments that can be independently adjusted and optimized, the system achieves sophisticated prioritization without overwhelming complexity in any single component.
Data Source
AI summary
A method for generating and prioritizing multiple search results is disclosed. A database stores search results in an information storage and retrieval system. A search program executes on a computer system coupled to the database. The search program receives a search request from a user input. The search program parses the search request into at least one search term. The search program performs a loop comprising steps associating a priority adjustment value with each search term, generating a search result, calculating a priority adjustment sum of the generated search result, inserting the at least one search term, the generated search result, and the calculated priority adjustment sum in the search result list, and modifying the at least one search term and the priority adjustment value associated with each search term to perform a next iteration of the loop.