Search Efficiency Quantification via Hyperlink Graph Weighting
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Solution Overview
Problem
Conventional methods for evaluating Web site effectiveness focus on traffic analysis, which fail to provide an objective measure of whether user information needs are met through searching features, leading to subjective user satisfaction assessments.
Innovation Solution
A system and method that uses a simulated user traffic flow analysis to evaluate search efficiency by building a directed graph of hyperlinks, assigning weights based on keyword relatedness, and applying equations to determine a quantitative measure of search efficiency, such as Ai=Ai−1·S, Ai=αAi−1·S, and Ai=Ai−1·S+E, to assess the likelihood of satisfying user information needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional traffic analysis methods are used to evaluate Web site effectiveness, then general user behavior statistics can be obtained, but objective measure of user information need fulfillment is lost
Solution Approach 1:
The patent introduces an intermediary computational model that processes search query data and hyperlink structure information to generate objective satisfaction metrics. This intermediary layer transforms raw traffic data into meaningful measurements of information need fulfillment, resolving the contradiction between obtaining general statistics and measuring specific user satisfaction.
Solution Approach 2:
The patent replaces subjective human evaluation of user satisfaction with an automated computational system that uses mathematical models to objectively measure whether user information needs are met. This substitution eliminates the loss of information inherent in subjective assessments while maintaining measurement precision through algorithmic analysis of search patterns and hyperlink traversal.
2Productivity
If click patterns are tracked to identify popular hyperlinks, then traffic flow information is obtained, but indication of user satisfaction with search results is lost
Solution Approach 1:
The patent implements feedback mechanisms where the computational model continuously analyzes user search behavior, hyperlink traversal patterns, and search query outcomes to refine satisfaction measurements. This feedback loop enables the system to distinguish between productive information retrieval (finding needed information) and unproductive browsing (wandering without satisfaction), thereby improving both productivity measurement and precision of search efficiency evaluation.
Solution Approach 2:
The patent changes the parameters used to evaluate Web site effectiveness from simple traffic counts to multi-dimensional metrics including search query relevance, hyperlink semantic relatedness, and user navigation patterns. These parameter changes enable simultaneous measurement of productivity (information retrieval efficiency) and precision (satisfaction accuracy) by analyzing multiple aspects of user interaction with the search system.
3Ease of operation
If subjective user satisfaction measures are used, then user feedback is captured, but quantitative assessment of information need fulfillment is lost
Solution Approach 1:
The patent enables the Web site evaluation system to self-assess its own effectiveness by automatically analyzing user search behavior and hyperlink structure without requiring explicit user feedback. This self-service approach maintains ease of operation (no additional user burden) while preventing loss of quantitative information about search efficiency, as the system autonomously generates objective satisfaction metrics from observed user interactions.
Solution Approach 2:
The patent substitutes explicit subjective user satisfaction surveys with implicit behavioral analysis that automatically quantifies information need fulfillment. By replacing direct user feedback mechanisms with automated analysis of search patterns and navigation behavior, the system maintains ease of operation (users simply browse normally) while capturing precise quantitative data about search efficiency and satisfaction without losing information.
Data Source
AI summary
A system and method for determining a quantitative measure of search efficiency of related Web pages. An information goal is specified. A target Web page is identified within a plurality of Web pages. The information goal is searched via a search function in the Web pages to identify potential Web pages that include at least one hyperlink referencing and proximal cues relating to distal content included in another potential Web page. An activation network is formed. A directed graph is built, including nodes corresponding to the potential Web pages and arcs corresponding to the hyperlinks. A weight is assigned to each arc to represent a probability of traversal of the corresponding hyperlink based on a relatedness of keywords in the information goal to the proximal cues. A traversal through the activation network to the node corresponding to the target Web page is evaluated as a quantitative measure of search efficiency.