Stationary Distribution Analysis for System Interaction Optimization
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Solution Overview
Problem
It is challenging to assess whether a system, such as a website, is optimally configured and to predict the effects of modifying its components, as existing methods lack effective tools for analyzing user interactions and determining the impact of altering linked items on overall system performance.
Innovation Solution
A computer-implemented method that determines a stationary distribution and conversion rate for a system of linked items, allows for the alteration of items based on this analysis, and outputs the results, including predicting the effect of removing items and determining altered transition probabilities to improve system performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods are used to assess system configuration, then system structure remains simple, but the ability to assess optimal configuration and predict modification effects is insufficient
Solution Approach 1:
The patent introduces a simulation system as an intermediary between the actual system and the assessment process. This simulation system models user interactions and system behavior, allowing indirect assessment of configuration effects without directly modifying or complexifying the actual system. The simulation acts as a mediator that captures system dynamics and enables prediction of modification outcomes.
Solution Approach 2:
The patent creates a copy of the system in the form of a simulation model that replicates key behaviors and interactions. This copy allows assessment and prediction activities to be performed on the model rather than the actual system, improving measurement precision while keeping the original system structure unchanged and simple.
2Measurement precision
If the system monitors and analyzes all user interactions, then conversion rate prediction improves, but data processing complexity and computational resources increase
Solution Approach 1:
The patent extracts only the essential and relevant features from comprehensive user interaction data that are necessary for conversion rate prediction. Instead of processing all raw interaction data, the system identifies and extracts key behavioral patterns and metrics that drive conversion, reducing data processing complexity while maintaining prediction accuracy.
Solution Approach 2:
The patent applies different levels of analysis and processing to different aspects of user interactions based on their importance. Critical interaction points that significantly influence conversion rates receive detailed analysis, while less important interactions are processed at a higher level or aggregated, creating a localized quality approach that balances precision with computational efficiency.
Data Source
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AI summary
There is described a computer-implemented method of outputting a result of an analysis of user interactions with a system of items, the method comprising: receiving input data relating to a system, which system comprises a plurality of linked items with at least one of the items being a session-ending item, wherein the input data relates to interactions of one or more users with the linked items; determining a stationary distribution for the system, wherein the stationary distribution indicates the probability of a user reaching each of the session-ending items; determining a conversion rate for the system based on the stationary distribution; altering and/or removing one of the items in dependence on the stationary distribution so as to form an altered system; determining an altered stationary distribution for the altered system; determining an altered conversion rate for the altered system; and providing an output in dependence on the outputting the altered system in dependence on the altered conversion rate being greater than the conversion rate.