video recommendation

DataFunSummit

Dec 22, 2023 · Artificial Intelligence

Cross‑Domain Multi‑Objective Estimation and Fusion in Baidu Video Recommendation: Design, Modeling, and System Evolution

This article shares Baidu's experience and thinking on cross‑domain multi‑objective estimation and fusion for video recommendation, covering background, system overview, multi‑objective design and modeling, long‑term value attribution, cross‑domain network architecture, and the evolution‑strategy based fusion approach.

BaiduCross-DomainRecommendation systems

0 likes · 13 min read

Cross‑Domain Multi‑Objective Estimation and Fusion in Baidu Video Recommendation: Design, Modeling, and System Evolution

DataFunTalk

Nov 29, 2023 · Artificial Intelligence

Cross-Domain Multi-Objective Estimation and Fusion in Baidu Video Recommendation

This article presents Baidu's technical experience on designing, estimating, and fusing cross-domain multi-objective models for its immersive video recommendation system, covering business background, system architecture, target design, long‑term value modeling, and evolution strategies.

AICross-DomainRecommendation systems

0 likes · 14 min read

Cross-Domain Multi-Objective Estimation and Fusion in Baidu Video Recommendation

DataFunSummit

Sep 29, 2023 · Artificial Intelligence

Social4Rec: Enhancing Video Recommendation with Social Interest Networks

This article introduces Social4Rec, a video recommendation algorithm that tackles user cold‑start problems by extracting and integrating social interest information through coarse‑ and fine‑grained interest extractors, attention‑based fusion, and extensive offline and online experiments demonstrating significant CTR improvements.

AttentionCold Startdeep learning

0 likes · 14 min read

Social4Rec: Enhancing Video Recommendation with Social Interest Networks

DataFunTalk

Jun 22, 2023 · Artificial Intelligence

Social4Rec: Social Interest Enhanced Video Recommendation Algorithm

Social4Rec introduces a social interest‑enhanced video recommendation framework that tackles user cold‑start by extracting coarse‑ and fine‑grained social interests via a self‑organizing neural network and meta‑path neighborhood aggregation, integrating these embeddings with a YouTube DNN model to improve CTR and AUC.

Cold Startctrdeep learning

0 likes · 14 min read

Social4Rec: Social Interest Enhanced Video Recommendation Algorithm

vivo Internet Technology

Mar 30, 2022 · Backend Development

Design of a Bloom Filter‑Based Video Recommendation Deduplication Service for Short Video Platforms

The paper proposes a Bloom‑filter‑based deduplication service for short‑video recommendation that moves three‑month playback histories to disk‑backed Bloom filters while keeping the latest 100 served IDs in Redis, employing write batching, sharding, expiration policies, and an incremental migration strategy to replace memory‑intensive Redis ZSets and dramatically reduce storage costs.

Bloom FilterDeduplicationRedis

0 likes · 21 min read

Design of a Bloom Filter‑Based Video Recommendation Deduplication Service for Short Video Platforms

iQIYI Technical Product Team

Dec 10, 2021 · Artificial Intelligence

GAN-based Cold-Start Solution for New Video Recommendation in Short Video Systems

iQIYI’s short‑video team solves the new‑video cold‑start problem by using a GAN that generates latent user features from video attributes and a discriminator to validate them, then matches these vectors to real users via cosine similarity, achieving double‑digit gains in exposure, CTR, and watch time.

Cold StartGANMachine Learning

0 likes · 13 min read

GAN-based Cold-Start Solution for New Video Recommendation in Short Video Systems

iQIYI Technical Product Team

Jun 4, 2021 · Artificial Intelligence

Intelligent Video Budget Pacing System for Online Video Platforms

An ecosystem‑wide intelligent promotion system applies a budget‑pacing algorithm with probabilistic throttling and fine‑ranking score adjustments in 5‑minute slots, guaranteeing uniform video exposure while minimizing impact on overall consumption, boosting daily exposure completion from under 5 % to up to 70 % and reducing watch‑time loss.

Content Distributionalgorithmbudget pacing

0 likes · 10 min read

Intelligent Video Budget Pacing System for Online Video Platforms

Tencent Cloud Developer

Nov 10, 2020 · Big Data

Design and Optimization of a Real-Time Video Recommendation Indexing System

The article describes a real‑time video recommendation indexing system that replaces 30‑minute batch builds with an Elasticsearch‑based service, integrates prior and posterior data pipelines, ensures consistency via locking and version checks, enables zero‑downtime upgrades, smooths write spikes, and boosts recall performance through multi‑level caching and ES tuning, delivering sub‑40 ms latency and significant business growth.

ElasticsearchFlinkPerformance Optimization

0 likes · 13 min read

Design and Optimization of a Real-Time Video Recommendation Indexing System

Youku Technology

Jun 15, 2020 · Artificial Intelligence

Multi-Objective Optimization for Guaranteed Delivery in Video Service Platforms

The paper proposes a two‑stage framework that first fits a differential‑equation‑based exposure‑click (P2C) model for each new video and then uses a genetic‑algorithm multi‑objective optimization to allocate scarce scene‑level exposure slots, simultaneously maximizing total views and halving CTR variance while outperforming manual baselines.

KDDODE modelingclick prediction

0 likes · 8 min read

Multi-Objective Optimization for Guaranteed Delivery in Video Service Platforms

Youku Technology

May 21, 2020 · Artificial Intelligence

Multi‑objective Optimization for Guaranteed Delivery in a Video Service Platform

The KDD 2020 paper from Alibaba Entertainment presents a differential‑equation‑based hot‑content exposure sensitivity model and a multi‑objective optimization framework that, under exposure‑resource constraints, guarantees video delivery by accounting for nonlinear content exposure, timing, strategies, and user click habits, now deployed on Youku.

KDD 2020differential equationsexposure modeling

0 likes · 2 min read

Multi‑objective Optimization for Guaranteed Delivery in a Video Service Platform

iQIYI Technical Product Team

May 8, 2020 · Artificial Intelligence

Introduction to NLP in Video Applications

When you browse video apps by tags, receive personalized recommendations, or search with keywords, the seamless experience is powered by Natural Language Processing, which analyzes and interprets textual data to connect users with relevant content, and the article invites you to scan a QR code for further exploration.

AI applicationsNLPNatural Language Processing

0 likes · 9 min read

Introduction to NLP in Video Applications

Tencent Cloud Developer

Jan 21, 2020 · Artificial Intelligence

Cold-Start Short Video Potential Prediction Using Siamese Networks

The paper proposes a Siamese‑based PredictionNet that combines EfficientB3 image and VGGish audio features with user metrics to predict a HotValue score for newly uploaded short videos, using a margin loss with view‑value‑aware pair selection, enabling tiered cold‑start exposure that boosts overall platform efficiency.

Cold StartMachine LearningSiamese network

0 likes · 9 min read

Cold-Start Short Video Potential Prediction Using Siamese Networks

iQIYI Technical Product Team

Jun 28, 2019 · Artificial Intelligence

iQIYI's RSLIME: A Novel Feature Importance Analysis Method for Video Recommendation Systems

iQIYI introduces RSLIME, a model‑agnostic, sample‑level feature importance method for its three‑stage small‑video recommendation system, enabling interpretable analysis of a complex ranking module that combines DNN, GBDT, and FM, and demonstrating stable, AUC‑correlated insights for optimization and feature selection.

DNNFMGBDT

0 likes · 11 min read

iQIYI's RSLIME: A Novel Feature Importance Analysis Method for Video Recommendation Systems

NetEase Media Technology Team

Apr 4, 2019 · Artificial Intelligence

Video Recommendation System: Framework, Topic Clustering, and Related Video Retrieval

The paper proposes a video recommendation framework that combines recall and ranking modules, using a multi‑modal topic clustering approach—integrating audio, visual, and textual features via NeXtVLAD, PCA, and K‑Means—to generate unified video representations, improve candidate selection, and boost click‑through and viewing time, while addressing cold‑start and semantic relevance challenges.

A/B testingNeXtVLADcold-start problem

0 likes · 7 min read

Video Recommendation System: Framework, Topic Clustering, and Related Video Retrieval

DataFunTalk

Dec 21, 2018 · Artificial Intelligence

Iterative Evolution of iQIYI Video Search Ranking Models

This article details iQIYI's practical experience in building and iterating its video search system, covering basic relevance, semantic matching via translation and click models, deep‑learning approaches, and ranking model evolution from heuristic rules to learning‑to‑rank, highlighting challenges, solutions, and performance gains.

Machine Learningdeep learninginformation retrieval

0 likes · 20 min read