Jan 20, 2024 · Artificial Intelligence

Decoding Xiaohongshu’s Recommendation System: How Ordinary Users Gain Visibility

Xiaohongshu’s recommendation system uses large‑scale multimodal embeddings, dual‑tower and graph models, and diversity techniques like DPP and SSD to quickly surface high‑quality user‑generated content, enabling ordinary users to gain visibility while balancing personalization, exploration, and efficient LLM‑augmented pipelines.

Large Language ModelsMultimodal AIXiaohongshu

0 likes · 15 min read

Decoding Xiaohongshu’s Recommendation System: How Ordinary Users Gain Visibility

Meitu Technology

Jun 25, 2018 · Artificial Intelligence

Meitu's Personalized Recommendation System: Architecture, Features, and Optimization Strategies

Meitu’s personalized recommendation platform for the Meipai app combines offline feature engineering, near‑real‑time streaming, and online serving to recall, estimate, and rank billions of short videos using multi‑modal content features, user profiling, online learning, cold‑start bandit strategies, and multi‑objective diversity optimization, delivering timely, diverse feeds across live, homepage, and video‑detail scenarios.

Online Learningcold startcontent diversity

0 likes · 17 min read

Meitu's Personalized Recommendation System: Architecture, Features, and Optimization Strategies