Let me continue with the matching algorithm code: matching-algorithm application/vnd.ant.code Personality-Based Matching Algorithm update // services/matchingService.js const User = require('../models/User'); const Match = require('../models/Match'); const MatchRequest = require('../models/MatchRequest'); const { calculateCompatibilityScore } = require('./compatibilityService'); /** * Find potential matches for a user * @param {String} userId - ID of the user to find matches for * @param {Number} limit - Maximum number of potential matches to return * @returns {Array} Array of potential matches with compatibility scores */ async function findPotentialMatches(userId, limit = 20) { try { // Get user's profile and preferences const user = await User.findById(userId); if (!user) { throw new Error('User not found'); } // Get user's existing matches and match requests to exclude them const existingMatches = await Match.find({ $or: [{ user1: userId }, { user2: userId }], status: { $in: ['active', 'paused'] } }); const sentRequests = await MatchRequest.find({ sender: userId, status: 'pending' }); const receivedRequests = await MatchRequest.find({ receiver: userId, status: 'pending' }); // Create list of users to exclude from potential matches const excludeUserIds = [ userId, // Exclude self ...existingMatches.map(match => match.user1.toString() === userId.toString() ? match.user2.toString() : match.user1.toString() ), ...sentRequests.map(req => req.receiver.toString()), ...receivedRequests.map(req => req.sender.toString()) ]; // Build query for finding potential matches const matchQuery = { _id: { $nin: excludeUserIds }, isActive: true, isVerified: true, // Filter by gender preferences gender: { $in: user.lookingFor }, lookingFor: { $in: [user.gender] } }; // Add age range filter if specified if (user.ageRangeMin && user.ageRangeMax) { const minDate = new Date(); minDate.setFullYear(minDate.getFullYear() - user.ageRangeMax); const maxDate = new Date(); maxDate.setFullYear(maxDate.getFullYear() - user.ageRangeMin); matchQuery.birthdate = { $gte: minDate, $lte: maxDate }; } // Find potential matches based on initial criteria const potentialMatches = await User.find(matchQuery) .select('_id displayName birthdate gender interests values personalityTraits communicationStyle location lastActive') .limit(limit * 2); // Get extra matches to filter down after scoring // Calculate compatibility scores for each potential match const scoredMatches = await Promise.all( potentialMatches.map(async match => { const compatibilityScore = await calculateCompatibilityScore(user, match); return { user: match, score: compatibilityScore, distanceKm: calculateDistance( user.location.coordinates, match.location.coordinates ), lastActive: match.lastActive }; }) ); // Sort by compatibility score and limit results return scoredMatches .sort((a, b) => b.score - a.score) .slice(0, limit); } catch (error) { console.error('Error finding potential matches:', error); throw error; } } /** * Calculate compatibility score between two users * This is imported from compatibilityService.js in the actual implementation * but included here for reference * * @param {Object} user1 - First user * @param {Object} user2 - Second user * @returns {Number} Compatibility score (0-100) */ function calculateCompatibilityScore(user1, user2) { // Initialize score components let personalityScore = 0; let interestsScore = 0; let valuesScore = 0; let communicationScore = 0; // 1. Personality traits comparison (40% of total score) // Compare each personality trait dimension const personalityTraits = [ 'openness', 'conscientiousness', 'extraversion', 'agreeableness', 'neuroticism' ]; let personalityDiffSum = 0; for (const trait of personalityTraits) { if (user1.personalityTraits.has(trait) && user2.personalityTraits.has(trait)) { // Calculate difference (0-1 scale) const diff = Math.abs( user1.personalityTraits.get(trait) - user2.personalityTraits.get(trait) ); personalityDiffSum += diff; } } // Convert difference to similarity score (0-40) personalityScore = 40 * (1 - (personalityDiffSum / personalityTraits.length)); // 2. Shared interests comparison (25% of total score) const user1Interests = new Set(user1.interests); const user2Interests = new Set(user2.interests); // Count shared interests let sharedInterests = 0; for (const interest of user1Interests) { if (user2Interests.has(interest)) { sharedInterests++; } } // Calculate interest score based on overlap percentage const totalInterests = Math.max(1, user1Interests.size + user2Interests.size - sharedInterests); interestsScore = 25 * (sharedInterests / totalInterests); // 3. Shared values comparison (25% of total score) const user1Values = new Set(user1.values); const user2Values = new Set(user2.values); // Count shared values let sharedValues = 0; for (const value of user1Values) { if (user2Values.has(value)) { sharedValues++; } } // Calculate values score based on overlap percentage const totalValues = Math.max(1, user1Values.size + user2Values.size - sharedValues); valuesScore = 25 * (sharedValues / totalValues); // 4. Communication style compatibility (10% of total score) // Predefined compatibility matrix for communication styles const communicationCompatibility = { 'direct': { 'direct': 1.0, 'thoughtful': 0.7, 'humorous': 0.8, 'deep': 0.6, 'casual': 0.7 }, 'thoughtful': { 'direct': 0.7, 'thoughtful': 1.0, 'humorous': 0.6, 'deep': 0.9, 'casual': 0.5 }, 'humorous': { 'direct': 0.8, 'thoughtful': 0.6, 'humorous': 1.0, 'deep': 0.7, 'casual': 0.9 }, 'deep': { 'direct': 0.6, 'thoughtful': 0.9, 'humorous': 0.7, 'deep': 1.0, 'casual': 0.5 }, 'casual': { 'direct': 0.7, 'thoughtful': 0.5, 'humorous': 0.9, 'deep': 0.5, 'casual': 1.0 } }; // Calculate communication style compatibility if (user1.communicationStyle && user2.communicationStyle) { const compatibilityValue = communicationCompatibility[user1.communicationStyle][user2.communicationStyle] || 0.5; communicationScore = 10 * compatibilityValue; } else { // Default if communication style not specified communicationScore = 5; } // Calculate total score (0-100) const totalScore = personalityScore + interestsScore + valuesScore + communicationScore; return Math.round(totalScore); } /** * Calculate distance between two points in kilometers * Using Haversine formula * * @param {Array} coords1 - [longitude, latitude] of first point * @param {Array} coords2 - [longitude, latitude] of second point * @returns {Number} Distance in kilometers */ function calculateDistance(coords1, coords2) { // Earth's radius in kilometers const R = 6371; const [lon1, lat1] = coords1; const [lon2, lat2] = coords2; // Convert to radians const dLat = (lat2 - lat1) * Math.PI / 180; const dLon = (lon2 - lon1) * Math.PI / 180; const a = Math.sin(dLat/2) * Math.sin(dLat/2) + Math.cos(lat1 * Math.PI / 180) * Math.cos(lat2 * Math.PI / 180) * Math.sin(dLon/2) * Math.sin(dLon/2); const c = 2 * Math.atan2(Math.sqrt(a), Math.sqrt(1-a)); const distance = R * c; return distance; } /** * Send a match request to another user * * @param {String} senderId - ID of the sending user * @param {String} receiverId - ID of the receiving user * @returns {Object} Created match request */ async function sendMatchRequest(senderId, receiverId) { try { // Check if users exist const [sender, receiver] = await Promise.all([ User.findById(senderId), User.findById(receiverId) ]); if (!sender || !receiver) { throw new Error('User not found'); } // Check if there's already a match between these users const existingMatch = await Match.findOne({ $or: [ { user1: senderId, user2: receiverId }, { user1: receiverId, user2: senderId } ], status: { $in: ['active', 'paused'] } }); if (existingMatch) { throw new Error('Match already exists between these users'); } // Check if there's already a pending request in either direction const existingRequest = await MatchRequest.findOne({ $or: [ { sender: senderId, receiver: receiverId }, { sender: receiverId, receiver: senderId } ], status: 'pending' }); // If receiver already sent a request to sender, create a match if (existingRequest && existingRequest.sender.toString() === receiverId.toString()) { existingRequest.status = 'accepted'; await existingRequest.save(); // Create a new match const newMatch = new Match({ user1: senderId, user2: receiverId, stage: 'text', stageStartDate: new Date(), status: 'active' }); await newMatch.save(); return { matchCreated: true, match: newMatch }; } // If sender already sent a request, return it if (existingRequest) { return { matchCreated: false, request: existingRequest }; } // Create a new match request const newRequest = new MatchRequest({ sender: senderId, receiver: receiverId, status: 'pending', sentAt: new Date() }); await newRequest.save(); return { matchCreated: false, request: newRequest }; } catch (error) { console.error('Error sending match request:', error); throw error; } } /** * Get recommended matches sorted by compatibility * For the app's home screen * * @param {String} userId * @param {Number} limit * @returns {Array} Recommended matches */ async function getRecommendedMatches(userId, limit = 10) { try { const potentialMatches = await findPotentialMatches(userId, limit * 2); // Apply additional filtering and sorting for recommendations const recommendedMatches = potentialMatches // Filter for higher compatibility .filter(match => match.score >= 60) // Sort by mix of compatibility and recency .sort((a, b) => { // Calculate a combined score that weights compatibility (70%) and recency (30%) const recencyScoreA = getRecencyScore(a.user.lastActive); const recencyScoreB = getRecencyScore(b.user.lastActive); const combinedScoreA = (a.score * 0.7) + (recencyScoreA * 0.3); const combinedScoreB = (b.score * 0.7) + (recencyScoreB * 0.3); return combinedScoreB - combinedScoreA; }) .slice(0, limit); return recommendedMatches; } catch (error) { console.error('Error getting recommended matches:', error); throw error; } } /** * Calculate recency score based on user's last activity * Returns a score 0-100 where 100 is most recent * * @param {Date} lastActive * @returns {Number} Recency score 0-100 */ function getRecencyScore(lastActive) { if (!lastActive) return 0; const now = new Date(); const hoursAgo = (now - lastActive) / (1000 * 60 * 60); // Score decreases as hours increase // Users active within last 24 hours get 80-100 // Users active within last week get 50-80 // Users active within last month get 10-50 // Others get 0-10 if (hoursAgo < 24) { return 100 - (hoursAgo / 24 * 20); } else if (hoursAgo < 168) { // 7 days return 80 - ((hoursAgo - 24) / 144 * 30); } else if (hoursAgo < 720) { // 30 days return 50 - ((hoursAgo - 168) / 552 * 40); } else { return Math.max(0, 10 - ((hoursAgo - 720) / 720 * 10)); } } module.exports = { findPotentialMatches, calculateCompatibilityScore, sendMatchRequest, getRecommendedMatches }; javascript
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