Collaborative Web Search Ranking via User Click Feedback
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Solution Overview
Problem
Intranet searches, such as corporate web searches, face challenges due to the absence or inadequacy of link structures, leading to unsatisfactory results and slow adaptation to dynamic changes, as traditional link-analysis algorithms are not applicable and fail to effectively prioritize relevant content.
Innovation Solution
A method and apparatus for collaborative web search that utilizes user feedback to rerank search results by employing a list optimizer, which considers implicit user endorsements based on the last click heuristic, combining textual match scores and adjustment values to produce a final result list, even in the absence of a link structure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If link-analysis algorithms are used for search ranking, then page importance can be determined through link structure analysis, but the system becomes slow to respond to dynamic changes and is not applicable when link structure is non-existent
Solution Approach 1:
The patent introduces a feedback mechanism where user click behavior is continuously monitored and fed back into the ranking system. The list optimizer uses implicit user endorsements (clicks) to dynamically adjust page rankings in real-time, allowing the system to adapt quickly to changing user preferences without relying on slow link structure updates
Solution Approach 2:
The system enables pages to self-promote through user clicks rather than requiring manual link updates. When users click on search results, the system automatically interprets this as an endorsement and adjusts rankings accordingly, allowing the ranking system to self-update based on actual user behavior patterns
2Measurement precision
If link-analysis algorithms are used for search ranking, then page importance can be calculated based on link structure, but the system fails when link structure is non-existent or defective
Solution Approach 1:
The patent creates a universal ranking system that works across different search environments with or without link structures. The list optimizer can function using either link analysis data when available or user click feedback when link structures are absent or defective, making the system adaptable to intranets, plain text searches, and hypertext searches alike
Solution Approach 2:
The patent introduces user click behavior as an intermediary signal that can replace link structure analysis. When link structures are unavailable or defective, the system uses user clicks as an alternative mediator to determine page importance, effectively substituting one ranking signal for another based on environmental conditions
3Ease of operation
If traditional search engines are used for intranet searches, then basic search functionality is provided, but the results are less than satisfactory due to poor link structure
Solution Approach 1:
The patent transforms the static ranking system into a dynamic one that continuously adapts based on user behavior. The list optimizer dynamically adjusts page rankings in real-time based on click patterns, allowing the system to respond to changing user preferences and improve result relevance over time rather than relying on fixed link structure analysis
Data Source
AI summary
Computer method and apparatus for collaborative web search operate in an intranet with non-existent or defective link structure. A search engine produces an initial search result list in response to a user query. A list optimizer reranks pages on the initial list based on implicit user recommendation or endorsement of pages. A last click heuristic defines user endorsement of a page. To form the final result list, the list optimizer scores each page according to reranking, a textual match (or information retrieval score) of the page with the query and an adjustment value.