CTR model | BestHub

Ximalaya Technology Team

Feb 20, 2024 · Artificial Intelligence

Optimization of Deep Learning-Based CTR Models in Advertising

This report presents recent advances in optimizing deep learning click‑through‑rate models for advertising, including improved embedding mechanisms, novel feature‑interaction and architecture designs such as attention‑based behavior sequencing, multi‑tower and Mixture‑of‑Experts networks, dynamic ID handling, hourly updates, incremental training, and outlines future multi‑modal and embedding‑importance research.

Advertising TechnologyCTR modelEmbedding Techniques

0 likes · 13 min read

Optimization of Deep Learning-Based CTR Models in Advertising

DataFunTalk

Feb 1, 2023 · Artificial Intelligence

Kuaishou Recommendation System: Architecture, CTR Modeling, Multi‑Domain Multi‑Task Learning, and Long‑Short Term Behavior Modeling

This article presents a comprehensive overview of Kuaishou's large‑scale recommendation system, detailing its pipeline, unique characteristics, CTR model improvements, the PPNet personalization network, multi‑domain multi‑task framework, short‑ and long‑term behavior sequence modeling, and the challenges of handling billions of features and trillions of parameters.

AICTR modelbehavior sequence modeling

0 likes · 12 min read

Kuaishou Recommendation System: Architecture, CTR Modeling, Multi‑Domain Multi‑Task Learning, and Long‑Short Term Behavior Modeling

DataFunSummit

Aug 5, 2022 · Artificial Intelligence

Kuaishou Short‑Video Recommendation System: Fine‑Grained Ranking Model Practices

This article details Kuaishou's practical advances in short‑video recommendation, covering the CTR PPNet model, multi‑domain multi‑task learning, short‑ and long‑term user behavior sequence modeling, and the resulting performance gains in user engagement and app usage.

AICTR modelKuaishou

0 likes · 7 min read

Kuaishou Short‑Video Recommendation System: Fine‑Grained Ranking Model Practices

DataFunTalk

Sep 14, 2020 · Artificial Intelligence

New Generation Rank Technology: Search‑Based Interest Model (SIM) and Dynamic Computation Allocation Framework (DCAF) for Alibaba Directed Advertising

This article presents Alibaba's latest ranking innovations for directed e‑commerce advertising, detailing the challenges of long‑term user interest modeling, the Search‑Based Interest Model (SIM) that extends behavior sequences to ten thousand actions, and the Dynamic Computation Allocation Framework (DCAF) that optimizes per‑request compute resources to maximize system revenue.

CTR modelMachine Learningadvertising

0 likes · 29 min read