This post briefly explains the core commercial AI system for Taobao and discusses how it has transformed the app into an "intelligent app".
This article deep-dives into "frontend", speaking on its evolution from ten years ago until now, and ten years into the future.
Pelajari bagaimana cara menggunakan salah satu feature machine learning Alibaba Cloud yang mudah digunakan: Alibaba Cloud Object Detection.
This article is based on the enterprise data lake construction solution using E-MapReduce and customer best practices shared by Ziguan.
This article discusses the newly introduced features and capabilities of Alibaba Cloud's machine learning platform, PAI.
This article explains how to build a personalized recommendation system by illustrating a news recommendation system using AnalyticDB for PostgreSQL.
This article explores how image recognition technology is used in AMAP data production for more accurate character and text recognition.
This article explains the main steps for training a machine and obtaining a model, provides some simple practices, and shares a basic principle of machine learning.
Hear 3 experts from the Alibaba Group and 2 researchers from Tsinghua University talk about recommendation algorithms and machine learning.
6 researchers explain the typical problems of query auto-completion with search engines and why the multi-view/multi-task attentive approach can be the solution.
Five researchers explore the audience competition for online TV series by providing the competitiveness definition, algorithm design, and experimental comparison.
This blog talks about Taobao's shop search service, and how Taobao successfully improved long-tail search performance with DHGAN.
6 researchers propose a controllable multi-interest framework for recommendation, which is used to recommend items based on a user's click sequence.
6 researchers explain benefits and challenges of graph representation learning.
This paper presents a new training method that allows the recommender to learn the user's next intention and more intentions to come.
We present the SGL learning framework to learn stable graph structures from heterogeneous confounded environments.
This article talks about the Gavotte model, which is used to automatically generate titles for buyer-uploaded videos in e-commerce scenarios.
This article introduces Graph Contrastive Coding (GCC), pre-training framework that uses the contrastive learning method to pre-train graph neural networks.
5 researchers propose the usage of a multi-task multi-view graph representation learning framework to learn node representations from multi-view graph...
10 Alibaba Cloud experts discuss feature input in prediction tasks and using PFD to maximize privileged features, particularly with Taobao recommendations.