Virtual Space Bidding via Potentiality Scoring
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Solution Overview
Problem
Existing virtual collaborative domains lack efficient methods for analyzing and optimizing the allocation of virtual spaces for content placement, leading to suboptimal engagement of users with virtual content in augmented reality environments.
Innovation Solution
A computer-implemented method and system for bidding on virtual spaces, which involves analyzing virtual collaborative domains to assign potentiality scores, conducting virtual auctions, and infusing a second virtual domain with the winning bidder's content, allowing seamless content display across multiple domains.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If virtual spaces are allocated without systematic analysis, then the allocation process is simple and quick, but the engagement of users with virtual content is suboptimal
Solution Approach 1:
The system performs preliminary analysis of virtual collaborative domains before content placement, calculating potentiality scores that predict user engagement. This advance preparation ensures high-quality content allocation without complexity during the actual placement operation, as the scoring framework is established beforehand
Solution Approach 2:
The patent introduces an intermediary potentiality scoring system that mediates between the simple act of content placement and the complex goal of optimizing user engagement. This intermediary layer translates domain characteristics into actionable scoring metrics that guide content allocation decisions
2Measurement precision
If virtual auctions are conducted without potentiality scoring, then the auction process is simpler and faster, but the allocation of virtual spaces is suboptimal
Solution Approach 1:
Potentiality scores are calculated in advance before auctions begin, providing precise evaluation metrics that guide bidding decisions. This preliminary scoring eliminates the need for complex real-time analysis during auctions, maintaining speed while improving allocation precision
Solution Approach 2:
The system transforms complex domain characteristics into a simplified potentiality score parameter that can be quickly compared and used in auction proceedings. This parameter transformation maintains measurement precision while reducing the time required for evaluation
3Productivity
If virtual content is placed without analyzing domain characteristics, then the content placement process is quicker, but the content is not displayed in high-traffic user-focused areas
Solution Approach 1:
The system performs preliminary analysis of domain characteristics and calculates potentiality scores that identify optimal content placement locations. This advance analysis ensures that content is placed in high-traffic areas without adding complexity to the actual placement execution
Solution Approach 2:
The potentiality scoring system provides feedback about domain characteristics and optimal placement locations, guiding content allocation decisions. This feedback mechanism ensures that placement efficiency is maintained while capturing crucial information about where content will be most effective
Data Source
AI summary
Techniques are described with respect to a system, method, and computer product for bidding on a virtual space. An associated method includes analyzing a first virtual collaborative domain and in response to the analysis, assigning a potentiality score of the virtual space for bidding of the first virtual collaborative domain. The method further including assigning a potentiality score of the virtual space for bidding of the first virtual collaborative domain; conducting a virtual auction for the virtual space; and in response to finalizing the virtual auction, infusing a second virtual collaborative domain with the first virtual collaborative domain.