How to Build a Scalable Dating App Backend: Architecture, Algorithms, and Performance Tips

This article explores the end‑to‑end design of a modern dating platform, covering requirement analysis, micro‑service architecture, gateway routing, sharded MySQL, CDN caching, matchmaking, recommendation scoring, high‑concurrency strategies, load balancing, database optimization, message queues, and spatial proximity algorithms such as grid, quadtree, and GeoHash.

cachingdatabase shardinghigh concurrency

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How to Build a Scalable Dating App Backend: Architecture, Algorithms, and Performance Tips

Amap Tech

Nov 19, 2020 · Big Data

Point Aggregation Algorithms for Map-based POI Data: Comparison, Implementation, and Evaluation

The article surveys and compares several point‑aggregation techniques for map‑based POI visualisation—including k‑means, grid‑based, grid‑centroid‑merge, grid‑distance, quad‑tree and KD‑tree methods—detailing their implementations, performance and clustering quality, evaluating them on a 175‑point dataset, and recommending the most suitable algorithm according to data size and required accuracy.

POI clusteringPerformance Evaluationmap visualization

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Point Aggregation Algorithms for Map-based POI Data: Comparison, Implementation, and Evaluation

Amap Tech

Jun 28, 2019 · Fundamentals

Road Matching: Definitions, Applications, and Key Algorithms

Road matching, a core subset of map‑matching theory, aligns GPS points to the correct road segments using algorithms such as distance‑based measures, Fréchet‑distance global optimization, and Hidden Markov Models, enabling accurate navigation, heterogeneous data fusion, traffic analysis, and urban planning, as validated by ACM SIGSPATIAL competitions.

Fréchet distanceGISHMM

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Road Matching: Definitions, Applications, and Key Algorithms

21CTO

Feb 19, 2016 · Artificial Intelligence

How to Achieve Accurate GPS Map Matching with ST‑Matching: A Practical Guide

This article reviews map‑matching challenges caused by GPS errors, categorizes existing algorithms, describes the ST‑Matching approach used on Washington State road data, and outlines key implementation techniques such as projection handling, memory‑pool loading, A* shortest‑path search, and localized indexing to improve accuracy and performance.

GPSST-Matchingmap matching

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How to Achieve Accurate GPS Map Matching with ST‑Matching: A Practical Guide