cross-domain learning

DataFunTalk

Jul 12, 2024 · Artificial Intelligence

Weak Supervision Machine Learning for Ant Group Business Scenarios: Methods, Experiments, and Applications

This article presents a comprehensive overview of weak supervision machine learning techniques applied to Ant Group's business problems, covering theoretical foundations, cross‑domain causal effect estimation, noisy‑label denoising frameworks, experimental results, and practical use cases such as risk modeling and marketing interventions.

Weak Supervisioncausal inferencecross-domain learning

0 likes · 16 min read

Weak Supervision Machine Learning for Ant Group Business Scenarios: Methods, Experiments, and Applications

DataFunTalk

Mar 17, 2024 · Artificial Intelligence

Leveraging Large Language Models to Enhance Comprehensive Graph Learning Capabilities

In this talk, researcher Jiang Zhuoren from Zhejiang University reviews the current state of large language models applied to graph learning, discusses their roles across various graph scenarios, and outlines promising research directions for unified cross‑domain graph learning.

artificial intelligencecross-domain learninggraph learning

0 likes · 3 min read

Leveraging Large Language Models to Enhance Comprehensive Graph Learning Capabilities

DataFunSummit

Jun 17, 2022 · Artificial Intelligence

Applying Knowledge Graphs to Meituan's Recommendation System

This talk explains how Meituan builds and leverages a massive lifestyle-domain knowledge graph to improve LBS recommendation, covering explicit and implicit graph applications, challenges such as explainability and data sparsity, and advanced models like dual‑memory networks and cross‑domain learning.

AIKnowledge GraphMeituan

0 likes · 15 min read

Applying Knowledge Graphs to Meituan's Recommendation System

DataFunTalk

May 16, 2022 · Artificial Intelligence

Applying Knowledge Graphs to Meituan's Recommendation System: Architecture, Challenges, and Future Directions

This article presents Meituan's large‑scale knowledge graph, its integration into location‑based recommendation, the challenges of explainability, domain diversity, data sparsity and spatiotemporal complexity, and describes a dual‑memory neural network and cross‑domain learning approach that improve recall, ranking and recommendation fairness.

AIKnowledge Graphcross-domain learning

0 likes · 15 min read

Applying Knowledge Graphs to Meituan's Recommendation System: Architecture, Challenges, and Future Directions

DataFunTalk

Aug 4, 2021 · Artificial Intelligence

Deep Learning Practices for Personalized Recommendation in a Cultural Artifact Auction Platform

This article presents a comprehensive case study of applying deep learning techniques—including item and user embedding, cross‑domain keyword intent modeling, and multi‑interest representation—to improve the recall stage of personalized recommendation for a cultural‑artifact auction platform, addressing unique data sparsity and diversity challenges.

cross-domain learningdeep learninge-commerce

0 likes · 16 min read

Deep Learning Practices for Personalized Recommendation in a Cultural Artifact Auction Platform