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Alibaba Terminal Technology
Alibaba Terminal Technology
Oct 27, 2021 · Mobile Development

How Youku Leverages HarmonyOS for Seamless Multi‑Screen Interaction

This article details Youku's strategic partnership with Huawei, explaining how HarmonyOS's distributed capabilities enable continuous and collaborative multi‑screen experiences such as seamless video flow, free‑view angles, and advanced casting, while also presenting the underlying architecture, protocols, and code implementations.

CastingHarmonyOSmulti-screen
0 likes · 20 min read
How Youku Leverages HarmonyOS for Seamless Multi‑Screen Interaction
Youku Technology
Youku Technology
Sep 17, 2019 · Frontend Development

Technical Deep Dive of the “Cool Watch” Mode Behind “The Longest Day in Chang’an”: Player Framework, Dynamic Rendering, and Multi‑Screen Synchronization

Alibaba Entertainment’s technical deep‑dive reveals how the “Cool Watch” mode for “The Longest Day in Chang’an” combines a plugin‑based player framework, dynamic Weex UI rendering, parent‑child screen architecture, and dual‑stream frame‑level synchronization—augmented by AI‑driven high‑resolution playback and anti‑theft linking—to deliver an immersive, multi‑screen interactive experience across Youku.

Weexdynamic renderingmobile video
0 likes · 14 min read
Technical Deep Dive of the “Cool Watch” Mode Behind “The Longest Day in Chang’an”: Player Framework, Dynamic Rendering, and Multi‑Screen Synchronization
21CTO
21CTO
Jul 31, 2019 · Artificial Intelligence

How JD Built a Scalable AI‑Powered Recommendation System

The article outlines JD’s evolution from rule‑based product suggestions in 2012 to a sophisticated, AI‑driven, multi‑screen personalized recommendation platform, detailing its product types, system architecture, data collection, offline and online computation, and the core recommendation engine that powers features like “Guess You Like.”

AIBig DataJD.com
0 likes · 14 min read
How JD Built a Scalable AI‑Powered Recommendation System
ITFLY8 Architecture Home
ITFLY8 Architecture Home
Jul 2, 2018 · Artificial Intelligence

How JD.com Built a Multi‑Screen Personalized Recommendation Engine

This article explains how JD.com evolved its recommendation system from simple product suggestions to a sophisticated, multi‑screen, multi‑type personalized engine using big‑data collection, real‑time behavior tracking, machine‑learning models, and a modular architecture that boosts conversion and user experience.

Big Datae‑commercemachine learning
0 likes · 14 min read
How JD.com Built a Multi‑Screen Personalized Recommendation Engine