User-Augmented Indexing for Search Relevance
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Solution Overview
Problem
Existing search engines rely on proprietary algorithms for indexing and ranking data, limiting user contribution and insight, making it difficult for users to find relevant information as decisions are made by singular authorities without public input, and failing to leverage collective user knowledge.
Innovation Solution
A method for creating a user-augmented index and ranking data entries, allowing users to categorize and designate values for data, enabling distributed user contributions and leveraging user insights for improved search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If search engines use proprietary algorithms to automatically index and rank data, then indexing speed and automation are improved, but user contribution and relevance accuracy deteriorate
Solution Approach 1:
The patent combines automated search engine indexing with manual user-contributed categories and ratings. The system merges machine-derived indexes with human-generated metadata, allowing both automated efficiency and user expertise to coexist. User categories and ratings are integrated into the search results, creating a hybrid system that leverages both automation and human judgment.
Solution Approach 2:
The system implements feedback loops where user interactions (ratings, category assignments) are collected and used to improve search results. User-provided feedback on data relevance is aggregated and influences ranking algorithms, creating a continuous improvement cycle that enhances search quality over time based on collective user experience.
2Device complexity
If search engines rely on singular authority decisions for indexing, then system simplicity is maintained, but adaptability to diverse user needs deteriorates
Solution Approach 1:
The patent segments the indexing authority into multiple independent contributors rather than a single centralized system. Each user contributes categories and ratings independently, and the system aggregates these segmented contributions. This segmentation allows diverse perspectives while maintaining a unified search interface, enhancing adaptability without overwhelming complexity.
3Loss of information
If users cannot contribute to indexing decisions, then system control is maintained, but loss of user knowledge and insights increases
Solution Approach 1:
The system enables users to self-serve by allowing them to directly contribute categories, tags, and ratings to the index. Users can independently add their knowledge and insights without requiring administrator intervention or complex approval processes. This self-service approach captures user knowledge while keeping the system easy to operate.
Data Source
AI summary
The application relates to a method for creating a user-augmented index, including: receiving information identifying data, a first user-created category and a first user-designated value from the first user. The data, the first user-created category, and the first user-designated value are associated together in a data entry in the user-augmented index. A second user-created category and a second user-designated value are received from the second user. The second user-created category and the second user-designated value are also associated with the data entry in the user-augmented index. The application further relates to ranking one or more related data entries in response to a query of a user-augmented index.