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Ele.me Technology
Ele.me Technology
Apr 10, 2025 · Artificial Intelligence

Ele.me Vertical Business AIGC Image Model: Architecture, Training Pipeline, and Evaluation

Ele.me created a domain-specific AIGC image model built from scratch on its own data using the DiT backbone, a three-stage training pipeline (transformer pre-training, prompt alignment, aesthetic fine-tuning), custom T5‑E‑CLIP text and visual encoders, ControlNet for layout control, and evaluated via FID, CLIP scores and a human rubric, enabling automated dish-image generation and UI asset creation for its vertical business.

AIGCControlNetDiT
0 likes · 8 min read
Ele.me Vertical Business AIGC Image Model: Architecture, Training Pipeline, and Evaluation
Alibaba Terminal Technology
Alibaba Terminal Technology
Mar 18, 2022 · Mobile Development

How Ele.me Boosted Holiday Sale Performance with PHA Hybrid App Framework

Ele.me tackled the performance and user‑experience challenges of its major sales events by replacing traditional H5 containers with the Progressive Hybrid App (PHA) framework, enabling native‑rendered TabBar, persistent WebViews, pre‑loading, location‑aware manifests, and comprehensive optimizations that cut first‑screen load times by hundreds of milliseconds.

Ele.meHybrid AppNative integration
0 likes · 14 min read
How Ele.me Boosted Holiday Sale Performance with PHA Hybrid App Framework
ITPUB
ITPUB
Dec 3, 2018 · Databases

How Ele.me Deployed a Dual‑Active Database System in Just Three Months

This talk details Ele.me’s three‑month rollout of a dual‑active (multi‑active) database system, covering design principles, architecture, migration steps, challenges such as data consistency and DDL handling, the tools built (DRC, D‑Bus, DCP, EMHA), and the performance and reliability benefits achieved.

DBAEle.medata replication
0 likes · 14 min read
How Ele.me Deployed a Dual‑Active Database System in Just Three Months
DataFunTalk
DataFunTalk
Nov 7, 2018 · Artificial Intelligence

Evolution of Ele.me Recommendation Algorithms and Online Learning Practice

This article outlines the background of Ele.me's recommendation business, details the evolution of its recommendation algorithms from rule‑based models to deep learning and online learning, and explains the practical implementation of real‑time data pipelines, feature engineering, model training, and deployment.

Ele.meOnline Learningmachine learning
0 likes · 13 min read
Evolution of Ele.me Recommendation Algorithms and Online Learning Practice
DataFunTalk
DataFunTalk
Oct 12, 2018 · Artificial Intelligence

Market Mechanisms and Control Measures in Ele.me Food Delivery Recommendation Algorithms

The article presents a comprehensive overview of Ele.me's food‑delivery recommendation system, detailing its business model, platform goals, unique challenges, market‑driven efficiency mechanisms, control strategies, system architecture, model evolution, and online‑learning techniques used to balance short‑term performance with long‑term ecosystem health.

AIEle.meOnline Learning
0 likes · 15 min read
Market Mechanisms and Control Measures in Ele.me Food Delivery Recommendation Algorithms
dbaplus Community
dbaplus Community
Jul 25, 2018 · Big Data

How Ele.me Built a Scalable Metadata Governance System for Big Data

This article explains how Ele.me tackles big‑data challenges by designing a metadata governance platform that collects SQL execution data, parses lineage with Antlr, stores graph relationships in Neo4j, and enables table/column lineage queries, DAG scheduling, and hot‑data analysis.

Data LineageEle.meSQL parsing
0 likes · 12 min read
How Ele.me Built a Scalable Metadata Governance System for Big Data
Ctrip Technology
Ctrip Technology
Jan 4, 2018 · Artificial Intelligence

Intelligent Scheduling and Pressure‑Balancing System at Ele.me: Machine‑Learning Applications

This article introduces Ele.me's intelligent scheduling platform, focusing on the pressure‑balancing subsystem and demonstrating how machine‑learning models such as rider capacity estimation and team pressure‑coefficient prediction are designed, trained, and deployed to improve real‑time O2O delivery operations.

Ele.meLogisticspressure balancing
0 likes · 14 min read
Intelligent Scheduling and Pressure‑Balancing System at Ele.me: Machine‑Learning Applications
21CTO
21CTO
May 9, 2017 · Backend Development

How Ele.me Scaled to 9M Daily Orders: Architecture, Service Splitting & Ops

This article explains how Ele.me grew from a student startup to handling over nine million daily orders by evolving its website architecture, adopting SOA, splitting services, implementing a robust release system, and building comprehensive monitoring and data‑access layers.

DeploymentEle.meService Splitting
0 likes · 13 min read
How Ele.me Scaled to 9M Daily Orders: Architecture, Service Splitting & Ops
System Architect Go
System Architect Go
May 8, 2017 · Frontend Development

Recap of Ele.me Frontend Technology Conference: PWA, Collaboration, Dependency Monitoring, Vue, Flow, and More

The author recounts attending Ele.me's front‑end technology conference, summarizing seven sessions covering PWA implementation, evolving front‑back collaboration, dependency health monitoring, Vue usage, Flow and type theory, design perspectives on Element, and the exploration of a visual document editor, while sharing personal impressions.

Ele.meFlowPWA
0 likes · 6 min read
Recap of Ele.me Frontend Technology Conference: PWA, Collaboration, Dependency Monitoring, Vue, Flow, and More