Search Engine Ranking Adjustment Using Clickstream Data
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Solution Overview
Problem
Current search engines rely on derivative evidence, such as link frequency, to determine the interest of web pages, which does not accurately reflect how interesting a document is to the user performing the search.
Innovation Solution
A method and system that uses direct evidence from clickstream data to adjust page rankings, incorporating measures like connectedness and velocity, which indicate how interesting a web page is to users, to provide more relevant search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If keyword frequency is used to rank web pages, then the ranking process is simple and fast, but the relevance to user interest is poor
Solution Approach 1:
The patent segments the ranking process into multiple independent components: keyword frequency analysis, link structure analysis, and clickstream behavior analysis. Each component processes different types of data separately and contributes to the overall ranking score, allowing the system to maintain speed while improving relevance through diversified evaluation criteria
Solution Approach 2:
The patent creates a composite ranking metric that combines multiple data sources (keyword frequency, link structures, and clickstream behavior) into a unified relevance score. This composite approach integrates diverse information types to achieve more accurate measurement of user interest while maintaining computational efficiency through structured data fusion
2Ease of manufacture
If link frequency is used to determine page interest, then the ranking system is easy to implement, but it provides only derivative evidence of user interest
Solution Approach 1:
The patent merges multiple evidence sources (link frequency data and clickstream behavior data) into a unified ranking system. By combining derivative evidence from links with direct evidence from user clickstream behavior, the system recovers lost information about actual user interest while maintaining implementation feasibility through integrated data processing
Solution Approach 2:
The patent introduces clickstream data as an intermediary that bridges the gap between link frequency and user interest. Clickstream behavior serves as a mediator that translates structural link information into direct evidence of user engagement, providing the missing direct user interest evidence without complicating the overall system architecture
3Measurement precision
If clickstream data is collected and analyzed to adjust rankings, then the relevance to user interest improves, but the system complexity increases
Solution Approach 1:
The patent makes the clickstream data collection system multi-functional by using the same data infrastructure for multiple purposes: tracking user behavior for ranking, analyzing navigation patterns, and monitoring engagement metrics. This universal approach reduces overall system complexity by consolidating data collection functions rather than creating separate systems for each function
Solution Approach 2:
The patent implements self-service mechanisms where the search system automatically collects, processes, and applies clickstream data without requiring external intervention. The system serves itself by continuously learning from user behavior and automatically adjusting rankings, reducing operational complexity while maintaining high measurement precision
Data Source
AI summary
A method and system for ranking Web pages in a Web search engine is described. One illustrative embodiment receives a Web search query from a particular user, the query including at least one keyword; identifies one or more Web pages that contain the at least one keyword; determines, for each of the one or more Web pages, a raw page ranking; adjusts the raw page ranking of each of at least one Web page among the one or more Web pages based on direct evidence of how interesting that Web page is to users to produce an adjusted page ranking, the direct evidence being derived from clickstream data collected from the users; and presents, as search results, the at least one Web page to the particular user in accordance with the adjusted page rankings.