Query Time Boosting Algorithm for Search Ranking
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Solution Overview
Problem
Current search engines do not allow application developers to customize the ranking of search results beyond the default relevance scores, limiting the ability to present the most relevant information to users based on specific criteria such as user preferences.
Innovation Solution
A query time boosting algorithm that enables application developers to modify relevance scores for search results using boost values, allowing for the customization of the ordered list presentation based on user-defined preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If search engines use default relevance scoring algorithms, then search results are generated quickly and consistently, but application developers cannot customize the ranking order to prioritize specific characteristics like ratings or pricing information
Solution Approach 1:
The patent segments the ranking process into two independent components: (1) the base search engine's relevance scoring algorithm, and (2) a separate boost value mechanism that applies customizable adjustments. This segmentation allows developers to customize ranking without modifying the core search engine, resolving the contradiction between adaptability and complexity.
Solution Approach 2:
The patent introduces boost values as an intermediary layer between the base relevance scores and the final ranking. These boost values act as a mediator that allows customization of ranking criteria (such as ratings, pricing, or other characteristics) without directly modifying the search engine's core algorithm, thereby enabling adaptability while maintaining system simplicity.
2Measurement precision
If application developers want to prioritize specific content characteristics like ratings or pricing, then user relevance is improved, but the search system requires additional customization parameters and processing
Solution Approach 1:
The patent enables precise relevance measurement by allowing developers to change parameters (boost values) associated with specific content characteristics. By adjusting these parameters, developers can precisely control the importance of factors like ratings or pricing in the final ranking, improving relevance measurement accuracy without requiring a completely complex new scoring system.
Data Source
AI summary
Systems and methods are provided for providing an ordered list of search results in response to a query. Consistent with certain embodiments, computer-implemented systems and methods may identify content items corresponding to a query. First relevance scores may be determined for the identified content items based on their relevance to the query. Second relevance scores may be determined by modifying at least one of the first relevance scores using a boost value. The boost value may be set to a default boost value when the query does not include an override boost value. The boost value may be set to the override boost value, when the query includes an override boost value. An ordered list of the identified content items may be generated based on the second relevance scores. The ordered list may be displayed on a display device.