Search Engine Ranking via User Feedback
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Solution Overview
Problem
Conventional search engines fail to accurately reflect user interests as they rely on complex algorithms that indirectly consider user preferences, often leading to irrelevant search results.
Innovation Solution
A system where users can actively rate, comment, and submit web content through a plug-in module, allowing human input to influence search rankings, with ratings and user-generated content being transmitted to a server computer to index and prioritize search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional search engines use complex algorithms to sort indexed content, then the system can process large volumes of web content automatically, but the search results do not accurately reflect user interests
Solution Approach 1:
The patent implements a feedback mechanism where users rate web content (e.g., as useful or not useful). The server computer collects these ratings and uses them to adjust the ranking of search results. This feedback loop enables the system to learn from user preferences and improve the accuracy of search results over time, directly addressing the problem of algorithms failing to reflect user interests.
Solution Approach 2:
The system enables users to actively participate in the search process by submitting ratings and feedback on web content they encounter. This user-generated feedback serves the system's purpose of improving search accuracy without requiring the system to complexly analyze user behavior patterns. The users themselves perform the evaluation function that would otherwise require sophisticated algorithms.
2Productivity
If search engines rely on automated web crawlers to index content, then the system can efficiently process vast amounts of web content, but it cannot capture real-time user preferences and interests
Solution Approach 1:
The patent introduces an intermediary component - the user feedback mechanism - that bridges the gap between automated content indexing and user preference capture. While web crawlers efficiently index content in the background, users act as intermediaries who provide preference information through ratings. This intermediary layer allows the system to maintain high indexing productivity while simultaneously capturing user preferences that automated systems miss.
3Measurement precision
If the system incorporates user ratings and feedback, then search results become more user-centric and relevant, but the system requires active user participation which may reduce ease of operation
Solution Approach 1:
The system allows users to provide feedback selectively rather than requiring constant interaction. Users can choose to rate content when they encounter it during browsing, but are not forced to do so for every search. This partial action approach maintains ease of operation for casual users while capturing sufficient feedback from active participants to improve search relevance for the community.
Data Source
AI summary
A search engine to index web content with user content. A server computer receives, from a first client computer operated by a first user, an identification of first web content displayed by a web browser of the first client computer in a main browser window. The identification of the first web content is transmitted by the first user to the server computer via a user interface separate from the main browser window. The server computer then indexes the first web content. In response to receiving a search query from a web browser of a second client computer operated by a second user, the server computer transmits search results to the web browser of the second client computer. The search results include the first web content identified by the first user in a position relative to identifications of other web content received from other users.