Matching System
This document describes the algorithmic matching system planned for post-MVP implementation.
Overview
The matching system will automatically suggest relevant connections between requests and offers based on:
- Semantic content analysis
- User preferences and history
- Geographic proximity
- Reputation scores
Matching Algorithms
Content-Based Matching
- Keyword analysis
- Tag similarity
- Category matching
- Semantic understanding
Collaborative Filtering
- User behavior patterns
- Similar user preferences
- Historical matching success
- Community trends
Contextual Matching
- Time sensitivity
- Geographic relevance
- Availability windows
- Resource constraints
Implementation Phases
Phase 1: Basic Tag Matching
- Simple tag-based suggestions
- Category filtering
- Manual feedback incorporation
Phase 2: Semantic Analysis
- Natural language processing
- Intent recognition
- Context understanding
Phase 3: Machine Learning
- Predictive matching
- Personalization algorithms
- Continuous improvement
User Interface
Matching Dashboard
- Suggested connections
- Matching confidence scores
- Quick action buttons
- Feedback mechanisms
Notification System
- Match alerts
- Preference updates
- Performance reports
Privacy Considerations
Data Usage
- Transparent matching criteria
- User-controlled preferences
- Opt-out mechanisms
- Data minimization
Consent
- Explicit matching consent
- Preference management
- Feedback control