Web Page Relevance Identification via Author Feedback
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Solution Overview
Problem
Search engines often provide outdated and irrelevant lists of web pages related to a selected file, as they rely on algorithms that fail to recognize changing noun phrases and do not effectively utilize author expertise, leading to a lack of relevance in search results.
Innovation Solution
A method where a system server identifies web pages related to a first file by generating inquiries based on author feedback, using citation-validation and natural language processing to rank web pages, and creating hyperlinks between the first file and selected web pages, influencing future search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If search engines use automated algorithms to generate related web pages, then the system operates efficiently with high productivity, but the relevance and accuracy of the results deteriorate due to inability to recognize changing noun phrases and author expertise
Solution Approach 1:
The system sends inquiries to authors of the original web page and authors of candidate related web pages, using their feedback responses to validate and refine the relevance of web pages. This human feedback loop corrects the inaccuracies of automated algorithms while maintaining reasonable processing speed through selective human review.
Solution Approach 2:
The patent introduces an intermediary validation layer between the automated search algorithm and the final search results. Authors act as intermediaries who review and confirm the relevance of web pages, bridging the gap between automated efficiency and human judgment accuracy.
2Quantity of substance
If search engines provide a large number of web pages to ensure comprehensive coverage, then the quantity of results increases, but the quality deteriorates due to inclusion of irrelevant results that are difficult to sort
Solution Approach 1:
Authors provide feedback on the relevance of each web page, enabling the system to filter out irrelevant results even from large sets. The feedback mechanism allows quality control without limiting the initial search breadth, as irrelevant pages can be identified and removed through author validation.
Solution Approach 2:
The system extracts and removes irrelevant web pages from the search results by using author feedback to identify and separate low-quality results from the comprehensive list, maintaining both quantity and quality.
3Device complexity
If search engines rely on existing algorithms without author input, then the system complexity remains low, but the adaptability to recognize changing noun phrases and subject matter deteriorates
Solution Approach 1:
Authors of web pages serve themselves by providing feedback on relevant related pages. This self-service approach allows the system to gain adaptability and recognition of changing terminology without requiring complex automated analysis systems, as domain experts naturally understand their own subject matter evolution.
Data Source
AI summary
Methods and systems for providing related web pages are disclosed. One method includes identifying a plurality of web pages, wherein the plurality of web pages each have a relationship with the first file, wherein the world wide web provides a platform for sharing web pages, and wherein each web page includes a document or information resource that is suitable for the world wide web and is accessible through a web browser. The method further includes generating a list of inquiries based on the plurality of web pages, providing, the list of inquiries to at least one author of the first file, receiving from the at least one author at least one response to the list of inquiries, selecting a subset of the plurality of web pages based on the at least one response, and storing information related to the selected subset of the plurality of web pages.