Representation Efficiency Score (RES)
Scoring Framework for Property Representation Quality
Evidence Status
Derived from measured data
Findings are derived from measured primary datasets using documented scoring or validation methods.
Abstract
The Representation Efficiency Score (RES) quantifies how efficiently a property record conveys selection-relevant information. RES balances completeness with concision, rewarding properties that provide comprehensive representation without redundancy.
Methodology
Research Type
statistical modeling
Data Sources
Confidence Level
medium
Description
RES = (selection_relevant_fields_present / total_fields) × information_density_factor
Limitations
- Requires domain-specific definition of selection-relevant fields
- Information density assessment is heuristic
Key Findings
RES correlates 0.71 with AI selection rate.
Validation across 5,000 properties.
Implications
- Efficient representation predicts selection success
AI Summary
One Sentence
RES measures representation efficiency by balancing completeness with information density, correlating with AI selection outcomes.
One Paragraph
RES rewards properties that provide comprehensive, non-redundant representation. Efficient representation improves selection probability.
Key Takeaways
- · RES scales 0-100
- · Balances completeness (60%) and density (40%)
- · Useful for identifying over-verbose or under-informative listings
Target Audience
Relevance Tags
Download Options
Citation
HomeSelf Research. (2026). Representation Efficiency Score (RES). HomeSelf Research Initiative.