multi‑interest

DaTaobao Tech

Jun 19, 2024 · Product Management

Multi‑Interest Vector Recall and PDN Models for Large‑Asset Recommendation in Alibaba Auction

Alibaba Auction improves large‑asset recommendation by deploying the multi‑interest vector recall model MIND and the two‑hop PDN model, adapting features and time weighting for unique, high‑value items, using hard‑negative sampling and combined rule‑based and vector similarity, which boosts conversion metrics while revealing filter‑bubble concerns.

E-commercePDNdeep learning

0 likes · 13 min read

Multi‑Interest Vector Recall and PDN Models for Large‑Asset Recommendation in Alibaba Auction

DataFunSummit

Apr 11, 2022 · Artificial Intelligence

Exploring QQ Music Recall Algorithms: Knowledge‑Graph Fusion, Sequence & Multi‑Interest Modeling, Audio Recall, and Federated Learning

This article presents a comprehensive overview of QQ Music's recall pipeline, detailing business characteristics, challenges such as noisy user behavior and cold‑start, and four major solutions—including knowledge‑graph‑enhanced recall, sequence‑based and multi‑interest modeling, audio‑based recall, and federated learning—along with practical insights and Q&A.

Audio EmbeddingFederated LearningKnowledge Graph

0 likes · 19 min read

Exploring QQ Music Recall Algorithms: Knowledge‑Graph Fusion, Sequence & Multi‑Interest Modeling, Audio Recall, and Federated Learning

DataFunTalk

Apr 3, 2022 · Artificial Intelligence

Exploring QQ Music Recall Algorithms: Knowledge‑Graph Fusion, Sequence & Multi‑Interest Modeling, Audio Recall, and Federated Learning

This article presents a comprehensive overview of QQ Music's recall system, detailing business scenarios, challenges such as noisy user behavior and cold‑start, and four key solutions—including knowledge‑graph‑enhanced recall, sequence and multi‑interest modeling, audio‑based recall, and federated learning—along with experimental results, deployment details, and a Q&A session.

Audio EmbeddingFederated LearningKnowledge Graph

0 likes · 20 min read

DataFunTalk

May 15, 2021 · Artificial Intelligence

Multi‑Interest Recall Techniques in iQIYI Short‑Video Recommendation

The article reviews the evolution of iQIYI's short‑video recommendation recall pipeline, detailing multi‑interest recall methods such as clustering‑based recall, MOE‑based recall, single‑activation multi‑interest networks, regularization strategies, dynamic capacity handling, and multimodal extensions, and discusses their impact on recommendation performance.

iQIYImachine learningmulti‑interest

0 likes · 15 min read

Multi‑Interest Recall Techniques in iQIYI Short‑Video Recommendation

DataFunTalk

Dec 24, 2019 · Artificial Intelligence

Evolution of Recall Models in Recommendation Systems: From Collaborative Filtering to Deep Learning and Tree‑Based Retrieval

This article surveys the development of recall modules in large‑scale recommendation systems, covering traditional item‑based collaborative filtering, single‑embedding DNN and dual‑tower approaches, multi‑interest capsule networks, graph‑based embeddings, long‑short term interest modeling, and the tree‑structured TDM framework for efficient deep matching.

deep learninggraph embeddingmulti‑interest

0 likes · 14 min read

Evolution of Recall Models in Recommendation Systems: From Collaborative Filtering to Deep Learning and Tree‑Based Retrieval