Dating Portal Development
A dating platform is an application for connecting people with matching algorithms, chat functionality, and security systems. Technically: media processing, real-time communications, recommendation engine. Business model: freemium with paid features (super likes, profile boost, advanced filters).
Profile and Media
Profile contains: photos (up to 9), brief description (bio), basic parameters (age, height, education, interests). Photo verification is a mandatory function:
- Selfie-verification: user takes a photo in specified pose → ML model compares with profile photos (DeepFace, FaceNet)
- Blue "verified" checkmark increases trust
Photo processing: automatic face detection (OpenCV or Cloud Vision API), warning if no clear face, crop + WebP conversion.
Matching Algorithm
Two approaches:
Swipe (Tinder model): user sees profiles one by one, swipes right (like) or left (skip). Match — both liked each other → chat opens.
Recommendation feed (Hinge model): daily candidates selected by algorithm. Less gamification, higher quality.
Ranking factors:
- Geographic proximity (PostGIS radius query)
- Parameter compatibility (age, interests)
- User activity (ELO-like rating based on who likes whom)
- Recent activity (online recently → higher)
ELO-rating: each user has internal "attractiveness" rating. Like from high-rated user increases your rating more than from low-rated (like chess).
def update_elo(liker_elo: float, liked_elo: float, mutual: bool) -> tuple:
k = 32
expected_liker = 1 / (1 + 10 ** ((liked_elo - liker_elo) / 400))
delta = k * ((1 if mutual else 0) - expected_liker)
return liker_elo + delta, liked_elo - delta
Real-time Chat
Chat opens only on match. WebSocket (Socket.io) for real-time message delivery. Features:
- Text, emojis, GIF
- Read/delivered (read receipts)
- Typing indicator
- Photos (with moderation before display)
Security and Moderation
Dating platforms are particularly vulnerable to fraud (catfishing, scams):
- Automatic detection of "fraudulent" patterns in text (external links, money requests)
- Block sending external links in first N messages
- Reports + quick blocking
- AI photo moderation (NSFW detector)
- Age verification for minors
Geolocation and Filters
Main filter — distance. PostGIS:
SELECT p.*, ST_Distance(p.location::geography, $user_location::geography) AS dist
FROM profiles p
WHERE p.id != $user_id
AND NOT EXISTS (SELECT 1 FROM swipes WHERE swiper_id = $user_id AND swiped_id = p.id)
AND ST_DWithin(p.location::geography, $user_location::geography, $radius_meters)
AND p.age BETWEEN $min_age AND $max_age
ORDER BY RANDOM() -- + ELO-weighting
LIMIT 20;
Monetization
- Super like — highlighted interest signal (N free, more — for coins)
- Boost — profile shown to more people for 30 minutes
- Rewind — undo last left swipe
- Advanced filters — by education, height, habits
- Unlimited likes (default daily limit applies)
- See who liked (without match)
Stripe Billing for subscriptions + in-app purchases via App Store/Google Play (30% platform fee).
Timeline
MVP (profiles, swipes, matches, chat, basic search): 4–5 months. Full platform with ELO, verification, video dating, monetization, mobile apps: 8–14 months.