Virtual Area Friendliness Computation for Online Environments
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Solution Overview
Problem
Users often select uninteresting virtual areas within a virtual world due to the lack of information about the friendliness level of these areas, which is not effectively communicated.
Innovation Solution
A system that detects external users entering a virtual world, computes joined user weightings for each area by aggregating friend-of-a-friend and commonality weightings, and provides a virtual area friendliness level, allowing users to select areas based on tailored parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the system provides multiple virtual area choices without friendliness level information, then the system complexity remains low, but users cannot make informed decisions and may select uninteresting areas
Solution Approach 1:
The system pre-calculates and stores friendliness level information for virtual areas before users need it. When a user enters the virtual world, the system has already computed the aggregated user weightings and friendliness levels for all available virtual areas, so this information is immediately available for display without adding computational burden at the moment of decision-making.
Solution Approach 2:
The patent introduces an intermediary computational layer that aggregates individual user weightings into a composite friendliness level metric. This intermediary representation simplifies the complex social dynamics of virtual areas into a single interpretable value that users can use to make decisions, bridging the gap between raw data and user-friendly information.
2Ease of operation
If the system computes and displays virtual area friendliness levels by aggregating user weightings, then users can make better area selections, but the computational complexity and processing time increase
Solution Approach 1:
The system segments the computation of friendliness levels by pre-calculating individual user weightings for each virtual area and storing them separately. When a user needs this information, the system aggregates only the relevant pre-computed weightings rather than performing full social network analysis from scratch, significantly reducing computational complexity while maintaining accuracy.
Solution Approach 2:
The patent transforms complex social relationship data into a simplified parameter (friendliness level) that captures the essential information users need. By changing the representation from detailed social graphs to aggregated numerical scores, the system makes the information easily computable and displayable without losing the ability to guide user decisions.
3Adaptability or versatility
If the system aggregates joined user weightings to compute friendliness levels, then the information becomes more personalized and relevant, but the data processing requirements increase
Solution Approach 1:
The system performs preliminary aggregation of user weightings and stores the results in advance. When users need personalized friendliness level information, the system retrieves and displays pre-computed values rather than performing real-time aggregation, maintaining personalization capability while avoiding the performance penalty of repeated computations.
Solution Approach 2:
The patent creates copies of aggregated friendliness level data and stores them in accessible locations within the system. Instead of re-computing the same aggregations multiple times for different users, the system maintains pre-computed copies that can be quickly retrieved and displayed, significantly improving data processing efficiency while preserving the ability to provide personalized information.
Data Source
AI summary
The invention described herein detects an external user entering into a virtual world that includes a virtual area. In turn, the invention described herein identifies a plurality of joined users that joined each virtual area and computes a joined user weighting for each of the plurality of joined users. The joined user weightings include friend of a friend level weightings and commonality weightings. Next, the invention described herein computes a virtual area friendliness level for each of the virtual areas by aggregating each of the joined user weightings for each of the virtual areas, and provides the virtual area friendliness levels to the external user in order for the external user to select the appropriate virtual area.