Tagged articles

candidate generation

3 articles · Page 1 of 1

Aug 31, 2026 · Artificial Intelligence

Multi-Path Recall Architecture: From Tag & Vector Search to Recall Manager Engineering

This article details the multi-path recall architecture in recommender systems, covering five recall sources (tag, vector, popularity, collaborative filtering, exploration), the Recall Manager's parallel scheduling and circuit breaking, engineering deployment pipelines with offline/online evaluation, and future trends like generative recall and joint optimization.

A/B testingANN vector searchRecall Manager

0 likes · 38 min read

Multi-Path Recall Architecture: From Tag & Vector Search to Recall Manager Engineering

21CTO

Jun 7, 2017 · Artificial Intelligence

How Pinterest Scaled Its Recommendation Engine: From Simple Graphs to Real‑Time AI Ranking

This article chronicles Pinterest's recommendation system evolution, detailing how the platform progressed from basic pin‑board co‑occurrence graphs to sophisticated machine‑learning‑driven candidate generation and real‑time personalized ranking, boosting user engagement and enabling advanced visual search capabilities.

AIPinterestcandidate generation

0 likes · 15 min read

How Pinterest Scaled Its Recommendation Engine: From Simple Graphs to Real‑Time AI Ranking

21CTO

Sep 8, 2015 · Artificial Intelligence

Inside Meituan’s Recommendation Engine: From Data to Real‑Time Ranking

This article outlines Meituan’s end‑to‑end recommendation system, describing its data layer, candidate‑generation triggers, fusion strategies, and machine‑learning‑based ranking models—including collaborative filtering, location‑based, query‑based, graph‑based methods, and both linear and non‑linear models—while highlighting practical optimizations such as AB testing, real‑time behavior handling, and fallback strategies.

Meituancandidate generationcollaborative filtering

0 likes · 19 min read

Inside Meituan’s Recommendation Engine: From Data to Real‑Time Ranking