video search | BestHub

Baidu Tech Salon

Jan 8, 2025 · Artificial Intelligence

Evolution of Video Search Ranking Architecture Toward an End‑to‑End Large‑Model Framework

The paper describes transforming a tightly coupled, multi‑stage video search ranking pipeline into a modular, end‑to‑end large‑model architecture that decouples recall, employs a graph‑engine parallel framework and elastic compute allocation, thereby boosting performance, flexibility, personalization and lowering long‑term operational costs.

Parallel Computingelastic resourcesend-to-end

0 likes · 10 min read

Evolution of Video Search Ranking Architecture Toward an End‑to‑End Large‑Model Framework

Baidu Geek Talk

Jan 8, 2025 · Artificial Intelligence

Evolution of Video Search Ranking Architecture Towards an End‑to‑End Large‑Model Framework

The article outlines how video search ranking has shifted from a tightly‑coupled multi‑stage cascade to an extensible, end‑to‑end, model‑centric framework called Rankflow, leveraging large‑model inference, decoupled recall, fine‑grained parallelism, and elastic compute allocation to boost performance, flexibility, and maintainability while paving the way for future retrieval‑augmented generation integration.

AILarge ModelsParallel Computing

0 likes · 11 min read

Evolution of Video Search Ranking Architecture Towards an End‑to‑End Large‑Model Framework

NetEase Cloud Music Tech Team

Jan 4, 2023 · Artificial Intelligence

Relevance Modeling and Ranking for Cloud Music Video Search

The paper details Cloud Music’s video‑search pipeline—query understanding, recall, relevance, ranking and re‑ranking—highlighting challenges such as ambiguous content, timeliness and multi‑objective goals, and describes two deployed models (a twin‑tower aspect relevance network and a click‑graph propagator) that together boost click‑through rate by 1.5 % and effective CTR by 2.3 %.

Cloud MusicRankingclick graph

0 likes · 24 min read

Relevance Modeling and Ranking for Cloud Music Video Search

DataFunTalk

Nov 16, 2020 · Artificial Intelligence

Deep Semantic Relevance and Multimodal Video Search at Alibaba Entertainment

The presentation by Alibaba Entertainment's senior algorithm expert details the challenges of video search in the 4G/5G era and describes a comprehensive framework covering business overview, relevance and ranking, multimodal retrieval, deep semantic modeling, dataset construction, and practical deployment techniques.

deep learninginformation retrievalmultimodal

0 likes · 27 min read

Deep Semantic Relevance and Multimodal Video Search at Alibaba Entertainment

DataFunSummit

Nov 3, 2020 · Artificial Intelligence

Deep Semantic Relevance and Multi‑Modal Video Search at Alibaba Entertainment

This presentation details Alibaba Entertainment's video search system, covering its business scope, user‑value metrics, a layered algorithm framework, relevance challenges, multi‑modal retrieval, deep semantic relevance techniques, model selection, asymmetric twin‑tower deployment, multi‑stage knowledge distillation, and practical effect cases.

Alibabadeep learningmultimodal

0 likes · 25 min read

DataFunTalk

Jul 8, 2020 · Artificial Intelligence

Multi‑Level Multi‑Modal Search Engine and Graph Engine for Video Content at Youku

The article presents a detailed technical overview of Youku's video search system, covering multi‑modal inputs, multi‑level element indexing, face search, cross‑level and cross‑modal retrieval, and the design and applications of a multimodal graph engine with knowledge‑graph integration.

AIface searchgraph engine

0 likes · 12 min read

Multi‑Level Multi‑Modal Search Engine and Graph Engine for Video Content at Youku

Youku Technology

Jun 8, 2020 · Artificial Intelligence

Video Search Technology and Multi-modal Applications at Alibaba Youku

Alibaba’s Youku video search platform combines six-layer architecture—data extraction, technology integration, recall, relevance, ranking, and intent understanding—leveraging CV, NLP, knowledge graphs, and multi‑modal cues such as face, OCR, and audio recognition to overcome title‑mismatch, entity, and semantic challenges and deliver precise, diverse video retrieval.

Natural Language Processinginformation retrievalknowledge graph

0 likes · 15 min read

Video Search Technology and Multi-modal Applications at Alibaba Youku

DataFunTalk

Apr 20, 2020 · Artificial Intelligence

Video Search at Youku: Algorithmic Practices, Relevance, Ranking, and Multimodal Techniques

This article presents a comprehensive overview of Youku's video search system, covering business background, evaluation metrics, system and algorithm frameworks, relevance and ranking feature engineering, dataset construction, semantic matching, multimodal video understanding, and practical case studies that illustrate the impact of deep learning and AI techniques on search performance.

AIRankingdeep learning

0 likes · 18 min read

Video Search at Youku: Algorithmic Practices, Relevance, Ranking, and Multimodal Techniques

Youku Technology

Mar 3, 2020 · Artificial Intelligence

Building a Quality Assurance System for Alibaba Video Search

To ensure stability and precision of Alibaba Youku’s massive video‑search platform, a three‑layer quality‑assurance framework was built—covering engineering regression and functional/effect monitoring, algorithmic data, UDF, feature‑column and index testing, effect baselines and impact assessment, plus user‑experience bad‑case mining and public‑opinion feedback loops.

AlibabaBig DataTesting

0 likes · 13 min read

Building a Quality Assurance System for Alibaba Video Search

Youku Technology

Feb 3, 2020 · Artificial Intelligence

Alibaba Entertainment Video Search Algorithms: Practice and Insights

In this talk, senior algorithm expert Ruo Ren outlines Alibaba Entertainment’s video‑search framework—covering basic relevance, ranking, and multimodal techniques that blend information retrieval, NLP, machine learning, and computer vision—using Youku as a case study to illustrate business needs, algorithmic challenges, and practical implementation solutions.

AI algorithmsAlibaba EntertainmentYouku

0 likes · 2 min read

Alibaba Entertainment Video Search Algorithms: Practice and Insights

DataFunTalk

Feb 3, 2020 · Artificial Intelligence

Alibaba Entertainment Search Algorithm Practice and Insights – Video Search Case Study with Youku

The live session presented Alibaba Entertainment’s senior algorithm expert discussing Youku’s video search business, relevance and ranking models, multimodal search challenges, and practical AI techniques, offering attendees a comprehensive view of modern video retrieval systems and their implementation.

AIinformation retrievalmachine learning

0 likes · 3 min read

Alibaba Entertainment Search Algorithm Practice and Insights – Video Search Case Study with Youku

iQIYI Technical Product Team

Jan 17, 2020 · Artificial Intelligence

Voice and Language Technologies in Natural Interaction: iQIYI HomeAI Speech Interaction System

The talk introduced iQIYI’s HomeAI platform, which combines user profiling (including voiceprint and age detection) with automatic video semantic extraction to enable natural, multi‑turn voice‑based video search—addressing hot‑content updates, contextual awareness, device environments, and personalized recommendations for screen‑less or accessibility‑focused users.

AINatural Language ProcessingSpeech Recognition

0 likes · 19 min read

Voice and Language Technologies in Natural Interaction: iQIYI HomeAI Speech Interaction System

Youku Technology

Apr 2, 2019 · Artificial Intelligence

How Youku Uses Multimodal AI for Video Understanding, Search, and Recommendation

Youku’s Algorithm Center has built a multimodal AI pipeline that jointly processes visual, audio, and textual signals to enhance video search, recommendation, and digital asset management, overcoming traditional keyword limits, improving relevance and cold‑start issues, while tackling fusion, cost, and interpretability challenges.

Recommendation systemscontent understandingmedia analytics

0 likes · 15 min read

How Youku Uses Multimodal AI for Video Understanding, Search, and Recommendation

Youku Technology

Oct 25, 2018 · Artificial Intelligence

Interview with Wang Xiaobo (Yongshu) on Large‑Scale Machine Learning, Recommendation Systems, and AutoML at Alibaba and Youku

At the AI Pioneer Conference, Wang Xiaobo, head of Alibaba’s Commercial Machine Intelligence and Youku’s algorithm teams, discussed large‑scale distributed learning, recommendation challenges such as cold‑start and video heterogeneity, AutoML innovations, multi‑modal search during promotions, and the future demand for specialists in few‑shot learning and domain adaptation.

AutoMLCold StartLarge-Scale Distributed Learning

0 likes · 21 min read

Interview with Wang Xiaobo (Yongshu) on Large‑Scale Machine Learning, Recommendation Systems, and AutoML at Alibaba and Youku