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Social-Aware Group Display Configuration in VR Conference
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Formulates the Social-Aware VR Conference Group Display Configuration (SVGD) problem for limited per-user display slots in VR conferences and proposes SVC, a 2-approximation greedy algorithm that picks preference or social configurations by effective ratio.
Problem
Large-scale VR conferences display too many irrelevant users on each attendee's HMD, harming experience; existing friend recommendation and cohesive group methods don't jointly handle personal preferences, social utility, co-display, and per-user display slot limits.
Approach
Defines SVD utility as a weighted fusion of personal preference and social utility (social counted only under mutual co-display), proves NP-hardness, and builds SVC, a greedy algorithm over a Quantified Social Benefit network that iteratively chooses P-Configuration or S-Configuration by effective utility ratio, with a 2-approximation guarantee.
Key results
- SVC outperforms 11 baselines by 75% on average in total SVD utility across datasets, with p-values below 0.05.
- SVC is proved to be a 2-approximation algorithm to SVGD with time complexity O(max_u(k_u)|V| log|E|).
- SVGD is proven NP-hard via reduction from Exact Cover by Three Sets.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use SVC instead of the evaluated baseline methods | SVGD · 5 real datasets | total SVD utility: 75% | Helped |
Limitations
- Does not account for users' view being obstructed by others, left as future extension
- Personal preferences and social utilities are assumed given or externally obtained rather than learned by the method
- Greedy approach yields only a 2-approximation guarantee
Experimental setup
Datasets: Timik Pokec Youtube SMMnet Facebook
Benchmarks: Timik Pokec Youtube SMMnet Facebook
Metrics: total SVD utility execution time p-value
Baselines: PER SOC RAND MAXD KOAVG SSGQ BCC MAXGF COMUR GraFrank FSGSel BF
Builds on: SVD utility weighted fusion of preference and social utility Quantified Social Benefit network
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