Online User Subset Selection for Match Quality
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Solution Overview
Problem
Computer-implemented games face challenges in providing a satisfactory multiplayer experience, particularly when players are mismatched, leading to unsatisfactory interactions due to large player bases and random selection methods.
Innovation Solution
A method and apparatus for selecting a subset of users in an online environment based on parameters such as geographic location, activity, and priority, allowing users to interact with others having similar characteristics, with dynamic updating of user subsets to ensure a desired number of matching players.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If random selection method is used to select players, then any player can be selected quickly, but player mismatch occurs leading to unsatisfactory interaction experience
Solution Approach 1:
The patent changes the selection parameters from completely random to based on multiple user attributes including geographic location, activity level, and priority status. This allows the system to filter and select users who meet specific criteria, improving match quality while maintaining reasonable selection speed through efficient parameter-based filtering.
Solution Approach 2:
The system performs preliminary actions by pre-categorizing users into queues based on their attributes (geographic location, activity, priority) before actual matching occurs. This preliminary organization enables faster retrieval of suitable candidates during the matching process, resolving the contradiction between selection speed and match quality.
2Adaptability or versatility
If a large number of users are available in the online environment, then user diversity increases, but selecting appropriate matching users becomes more difficult
Solution Approach 1:
The patent segments the large user base into distinct queues based on geographic location, activity level, and priority status. This segmentation organizes the diverse user population into manageable groups, making the selection process simpler while preserving user diversity within each segment.
Solution Approach 2:
The system applies local quality by creating different queues with specific characteristics (e.g., geographic regions, activity levels). Each queue has tailored properties that make user selection more straightforward within that local context, reducing overall system complexity while maintaining diversity across all queues.
Data Source
AI summary
A method comprises the steps of: selecting in a server, a subset of a plurality users of an online environment for a first user, wherein when in said online environment, said first user interacts with one or more users of said subset of the plurality users.