Dynamic In-Game Option Weighting System
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Solution Overview
Problem
In computer-implemented social or casual gaming, it is challenging to analyze and quantify the effectiveness of in-game options and user interfaces to keep players engaged, as various factors such as language, geography, and presentation style influence selection and engagement, making it difficult to determine the success of these elements.
Innovation Solution
A computer system that stores options and sub-options with unique identifiers and weights, allowing the processor to retrieve and update these based on user selections, using the weights to control the display and selection of options, thereby improving user interaction and engagement by monitoring and analyzing user preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple in-game options are provided to users, then user engagement and interaction opportunities increase, but it becomes difficult to analyze and quantify the effectiveness of each option
Solution Approach 1:
The system implements feedback by tracking user selections of in-game options and using this data to update weights. The processor monitors which options users choose and feeds this information back into the weighting system, allowing continuous improvement of option selection based on actual user behavior patterns.
Solution Approach 2:
The system changes parameters by dynamically adjusting weights assigned to different in-game options based on user selection data. These weight parameters are modified continuously as more user interactions are collected, allowing the system to adapt to changing user preferences and optimize engagement.
2Measurement precision
If user selection data is collected and analyzed, then option effectiveness can be measured, but system complexity increases
Solution Approach 1:
The system performs self-service by automatically collecting user selection data, processing it through the weighting algorithm, and updating option weights without requiring external manual analysis. The processor autonomously manages the entire workflow from data collection to weight adjustment.
Solution Approach 2:
The system achieves multi-functionality by combining data collection, analysis, weight calculation, and option selection into a single integrated system. The same processor that manages game operations also handles the analytics and weight updates, eliminating the need for separate dedicated systems.
3Ease of operation
If weights are dynamically updated based on user selections, then option presentation can be optimized, but data processing requirements increase
Solution Approach 1:
The system applies partial action by updating weights incrementally based on each user selection rather than recalculating all weights from scratch. This approach processes only the necessary data changes, reducing overall computational requirements while maintaining optimization effectiveness.
Data Source
AI summary
A computer system has at least one memory and at least one processor. The at least one memory stores one or more options. Each option is associated with a gaming application provided to a user device. Each option has a respective identifier and a respective weight. The at least one processor retrieves one or more of the options from the at least one memory. The weight provides a weighting for each option in dependence on previous selections of that option.