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DataFunTalk

Dec 29, 2021 · Artificial Intelligence

Entity Alignment in Product Knowledge Graphs: Techniques and Applications

This article presents a comprehensive overview of building and applying product knowledge graphs for e‑commerce, covering background, recent advances in graph neural network‑based entity alignment, online prediction pipelines, data construction, evaluation metrics, attribute extraction, and future research directions.

attribute extractione-commerceentity alignment

0 likes · 23 min read

Entity Alignment in Product Knowledge Graphs: Techniques and Applications

DataFunTalk

Dec 12, 2021 · Artificial Intelligence

Commercial Recommendation System for 58 Recruitment: Architecture, Recall, and Ranking Techniques

This talk presents the design and implementation of 58’s commercial recruitment recommendation system, covering the characteristics of the app’s recommendation scenario, system architecture, region‑based and behavior‑based recall methods, and coarse‑ and fine‑ranking models with various optimizations and future directions.

AIMachine Learninge-commerce

0 likes · 20 min read

Commercial Recommendation System for 58 Recruitment: Architecture, Recall, and Ranking Techniques

DataFunTalk

Dec 8, 2021 · Artificial Intelligence

NLG Solutions for E‑Commerce: DAMO Academy’s XGeneration, Word2Text, KG2Text, and Metaphor Generation

This talk presents DAMO Academy’s end‑to‑end NLG pipeline for e‑commerce, detailing the XGeneration content‑reproduction system, controllable short‑text generation models (PKM and PSCN), knowledge‑graph‑to‑text generation, metaphor generation, and their extensions to short‑video script creation and intelligent video editing, together with performance results and practical applications.

Metaphor GenerationNLGVideo Script

0 likes · 12 min read

NLG Solutions for E‑Commerce: DAMO Academy’s XGeneration, Word2Text, KG2Text, and Metaphor Generation

DataFunTalk

Nov 2, 2021 · Artificial Intelligence

Personalized Recommendation and Advertising Algorithms for E‑commerce: Business Overview, Recall and Ranking Optimization, Multi‑Task Modeling, and Future Directions

This article presents a comprehensive technical overview of JD.com’s e‑commerce recommendation and advertising systems, covering business scenarios, recall optimizations (profile and similarity‑based), multi‑task ranking improvements, sample weighting, multi‑model ensembles, PID‑based CPC control, conversion‑delay modeling, and the achieved performance gains and future research plans.

CTR optimizationMachine LearningRecommendation Systems

0 likes · 18 min read

Personalized Recommendation and Advertising Algorithms for E‑commerce: Business Overview, Recall and Ranking Optimization, Multi‑Task Modeling, and Future Directions

DataFunTalk

Oct 21, 2021 · Artificial Intelligence

Exploration of Alibaba's Feizhu Recommendation Algorithms and Full‑Space CVR Estimation Models (ESMM, ESM², HM³)

This article presents a comprehensive overview of Alibaba's recommendation algorithm practice for the Feizhu travel platform, covering the evolution of e‑commerce recommendation frameworks, full‑space CVR estimation models such as ESMM, ESM² and HM³, and the specific challenges and solutions for travel‑centric recommendation scenarios.

AlibabaCVR estimationFull‑Space Modeling

0 likes · 25 min read

Exploration of Alibaba's Feizhu Recommendation Algorithms and Full‑Space CVR Estimation Models (ESMM, ESM², HM³)

DataFunTalk

Sep 30, 2021 · Artificial Intelligence

Advances in Knowledge Graph Construction and Applications by Alibaba's AliMe Team

This article presents Alibaba's AliMe team's year‑long progress on knowledge graph research, covering the fundamentals of knowledge graphs, domain and multimodal graph construction techniques, practical e‑commerce applications such as dialogue‑driven recommendation, virtual‑anchor script generation, and insights on future directions.

AIdialogue systeme-commerce

0 likes · 23 min read

Advances in Knowledge Graph Construction and Applications by Alibaba's AliMe Team

DataFunTalk

Aug 17, 2021 · Artificial Intelligence

Intelligent Data Assistant for Alibaba Live Streaming: Features, Architecture, and Business Impact

The article describes Alibaba's intelligent data assistant for live streaming, detailing streamer needs, the product's real‑time and post‑live reporting features, AI‑driven insights, the underlying big‑data architecture, and a rigorous experiment that demonstrates significant sales uplift and efficiency gains.

AIBig DataReal-time

0 likes · 18 min read

Intelligent Data Assistant for Alibaba Live Streaming: Features, Architecture, and Business Impact

DataFunTalk

Aug 7, 2021 · Artificial Intelligence

Multi-Category Mixture-of-Experts Model for JD Search Ranking

This article presents a multi‑category Mixture‑of‑Experts (MoE) approach for e‑commerce search ranking, addressing category‑specific behavior and small‑category learning by introducing hierarchical soft constraints and adversarial regularization, and demonstrates significant AUC and NDCG gains on Amazon and JD in‑house datasets.

Adversarial RegularizationHierarchical Soft ConstraintMachine Learning

0 likes · 10 min read

Multi-Category Mixture-of-Experts Model for JD Search Ranking

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.

Deep LearningFaisscross-domain learning

0 likes · 16 min read

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

DataFunTalk

Jul 10, 2021 · Artificial Intelligence

Multi‑Business Ranking Modeling and Optimization in Meituan Search

This article presents Meituan's multi‑business search ranking system, describing the challenges of mixed‑business queries, the layered architecture, the evolution of multi‑business quota models (MQM‑V1/V2) and multi‑business ranking networks (MBN‑V1‑V4), experimental results, and future research directions.

Deep LearningMeituane-commerce

0 likes · 16 min read

Multi‑Business Ranking Modeling and Optimization in Meituan Search

DataFunTalk

May 19, 2021 · Artificial Intelligence

Causal Inference for Optimizing Advertising Budget Allocation in Fliggy Search CPC Ads

This article explains how causal inference techniques are applied to model the uplift effect of ad placement in Alibaba's Fliggy search CPC advertising, transforming budget allocation into a multi‑objective optimization problem and describing practical control methods, feature engineering, sample re‑sampling, model designs, uplift evaluation, and future research directions.

Machine LearningUplift modelingadvertising

0 likes · 18 min read

Causal Inference for Optimizing Advertising Budget Allocation in Fliggy Search CPC Ads

DataFunTalk

May 8, 2021 · Artificial Intelligence

Attribute‑Level Sentiment Analysis for E‑commerce: Tasks, Challenges, and System Design

This article presents a comprehensive overview of sentiment analysis in user‑generated content, detailing document‑, sentence‑, and aspect‑level tasks, defining the Aspect Sentiment Triplet Extraction problem for e‑commerce reviews, describing a three‑stage pipeline with pre‑training, multi‑domain modeling and attribute normalization, and reporting significant business improvements such as 400% CTR lift, while also discussing data imbalance, annotation scarcity, and future research directions.

Machine Learningaspect‑based sentimente-commerce

0 likes · 15 min read

Attribute‑Level Sentiment Analysis for E‑commerce: Tasks, Challenges, and System Design

DataFunTalk

Apr 4, 2021 · Big Data

User Profiling: Concepts, Practices, and Data‑Driven E‑Commerce Case Study

This article introduces the fundamentals of user profiling, explains tag types and their business value, and demonstrates a data‑driven e‑commerce case study that analyzes gender, age, region, marital status, education, profession, product preferences, purchase timing, and price sensitivity to guide targeted promotion strategies.

Big Datadata analysise-commerce

0 likes · 16 min read

User Profiling: Concepts, Practices, and Data‑Driven E‑Commerce Case Study

DataFunTalk

Apr 3, 2021 · Artificial Intelligence

A Survey of User Behavior Sequence Modeling for Search and Recommendation Advertising

User behavior sequence modeling, crucial for search and recommendation advertising ranking, has evolved from simple pooling to attention, RNN, capsule, and Transformer architectures, with industrial applications across e‑commerce, social, video, and music platforms, and future directions include time‑aware, multi‑dimensional, and self‑supervised approaches.

Deep LearningRecommendation SystemsTransformer

0 likes · 24 min read

A Survey of User Behavior Sequence Modeling for Search and Recommendation Advertising

DataFunTalk

Jan 8, 2021 · Artificial Intelligence

Deconstructing E‑commerce Recommendation Systems: Architecture, Challenges, and Strategies

This article provides a comprehensive overview of e‑commerce recommendation systems, detailing their end‑to‑end workflow, key challenges such as multi‑scenario objectives and data loops, core components like recall and ranking, model evolution, feature engineering, evaluation metrics, and practical considerations for building a healthy, multi‑objective recommendation ecosystem.

Data EngineeringMachine Learninge-commerce

0 likes · 17 min read

Deconstructing E‑commerce Recommendation Systems: Architecture, Challenges, and Strategies

DataFunTalk

Nov 4, 2020 · Artificial Intelligence

Intelligent E‑commerce Search: Architecture, Techniques, and Real‑World Impact

This article explores the evolution of e‑commerce search, detailing why search matters, the technical pipeline—including query preprocessing, entity and intent recognition, knowledge‑graph construction, recall, coarse and fine ranking—and demonstrates substantial performance gains through real‑world case studies.

AIInformation RetrievalMachine Learning

0 likes · 16 min read

Intelligent E‑commerce Search: Architecture, Techniques, and Real‑World Impact

DataFunTalk

Nov 2, 2020 · Product Management

Applying User Profiling Across the User Lifecycle to Optimize E‑commerce Product Chains

This article explains how user profiling, using models like AARRR and RARRA, can be applied at each stage of the user lifecycle—pre‑acquisition, active use, and post‑churn—to enhance e‑commerce product chain optimization through data‑driven insights, channel selection, and personalized services.

AARRRRARRAdata-driven optimization

0 likes · 13 min read

Applying User Profiling Across the User Lifecycle to Optimize E‑commerce Product Chains

DataFunTalk

Oct 1, 2020 · Artificial Intelligence

Building and Applying a Vector System for Search and Recommendation at NetEase Yanxuan

This article describes how NetEase Yanxuan has designed, trained, and deployed a unified vector representation system to power various e‑commerce search and recommendation scenarios, covering model choices, incremental learning strategies, large‑scale similarity computation, and practical lessons from real‑world deployments.

Machine Learninge-commercelarge-scale similarity

0 likes · 18 min read

Building and Applying a Vector System for Search and Recommendation at NetEase Yanxuan

DataFunTalk

Oct 4, 2020 · Artificial Intelligence

Reinforcement Learning for Product Ranking: Model Design, Experiments, and Online Deployment

This article presents a comprehensive study of using reinforcement learning to improve e‑commerce product ranking, covering the limitations of traditional scoring, the design of context‑aware models, a pointer‑network based sequence generator, various RL algorithms, extensive offline evaluations, and successful online deployment with future research directions.

Deep LearningPPOe-commerce

0 likes · 28 min read

Reinforcement Learning for Product Ranking: Model Design, Experiments, and Online Deployment

DataFunTalk

Sep 19, 2020 · Artificial Intelligence

AliCoCo: Alibaba’s E‑commerce Cognitive Concept Net – Architecture, Construction, and Applications

The article presents AliCoCo, Alibaba’s large‑scale e‑commerce knowledge graph that models user demand as concepts, describes its four‑layer architecture, the algorithms for concept extraction, taxonomy building, and item association, and demonstrates its impact on search and recommendation systems.

AlibabaNLPconcept extraction

0 likes · 22 min read

AliCoCo: Alibaba’s E‑commerce Cognitive Concept Net – Architecture, Construction, and Applications