Webpage Personalization via Cyclic Dependency Resolution
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Solution Overview
Problem
Existing systems face performance bottlenecks when retrieving search results due to increased system resource demand, leading to a slow user experience, particularly on eCommerce websites, where numerous user actions and item activities retrieve excessive database information, necessitating a method to enhance efficiency and reduce resource usage.
Innovation Solution
The system models a webpage as a random field using an undirected graph with nodes and edges, where each edge has a compatibility function based on goodness functions, allowing for the determination of a probability threshold to optimize webpage display and personalize user experiences by breaking cyclic dependencies and iteratively processing inferences to improve user interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional search result retrieval systems are used, then system bandwidth usage increases and user experience deteriorates, but implementing whole page personalization requires handling cyclic dependencies which increases system complexity
Solution Approach 1:
The patent segments the webpage into multiple modules (header, navigation, product display, footer, etc.), where each module can be independently personalized and rendered. This segmentation allows the system to handle cyclic dependencies at the module level rather than requiring complete page re-rendering, thereby improving retrieval efficiency while managing complexity through modular architecture
Solution Approach 2:
The system performs preliminary actions by pre-computing compatibility scores and personalization parameters for each webpage module before actual search result retrieval. Cyclic dependencies are identified and resolved in advance during the module configuration phase, allowing the main search retrieval process to operate without being blocked by dependency resolution overhead
2Loss of energy
If whole page personalization is implemented to improve user experience and reduce bandwidth demand, then the system must model webpages as random fields with cyclic dependencies, increasing computational complexity
Solution Approach 1:
By dividing the webpage into independent modules with defined compatibility relationships, the system reduces the computational scope of random field modeling from the entire page to individual modules and their immediate neighbors. This segmentation allows parallel processing of module personalization while maintaining overall page coherence through compatibility functions
Solution Approach 2:
The system implements partial personalization by focusing computational resources on personalizing only the most impactful webpage modules (such as product display and recommendations) rather than uniformly personalizing every element. This selective approach reduces bandwidth demand and computational complexity while still achieving meaningful user experience improvement
3Ease of operation
If cyclic dependencies in webpage elements are not managed, then user experience deteriorates due to inefficient personalization, but implementing dependency management increases processing time
Solution Approach 1:
The system employs periodic action by implementing iterative inference algorithms that cycle through webpage modules multiple times, progressively resolving cyclic dependencies. Each iteration refines the personalization of modules based on updated compatibility scores from previous iterations, eventually converging to a stable configuration that satisfies user experience requirements without requiring excessive processing time
Data Source
AI summary
A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when run on the one or more processors, cause the one or more processors to perform functions including: reconfiguring a webpage as an undirected graph; identifying a cyclic dependency in the undirected graph; iterating processing one or more inferences over the cyclic dependency for each pair of the nodes of the set of the nodes; breaking one or more of edges of the undirected graph; determining, based at least in part on compatibility functions of the one or more edges remaining after breaking the one or more of the edges, a probability of the webpage having exceeded a predetermined threshold to cause a user to take an action; and sending instructions to display the webpage. Other embodiments are described.