position bias | BestHub

NetEase Yanxuan Technology Product Team

Aug 15, 2022 · Artificial Intelligence

Evolution of the First-Focus Personalized Recommendation Model in E-commerce

The article details a step‑by‑step evolution of an e‑commerce platform’s top‑slot recommendation system, moving from a DCN‑mix single‑objective model through BST‑based dynamic features, position‑bias debiasing, multi‑task MMoE learning, and finally BST with target‑attention, each yielding measurable CTR, conversion, and user‑value gains.

CTR predictionE-commercedeep learning

0 likes · 22 min read

Evolution of the First-Focus Personalized Recommendation Model in E-commerce

DataFunTalk

Jan 25, 2021 · Artificial Intelligence

Evolution of Zhihu Search Ranking Models: From GBDT to DNN, Multi‑Goal and Context‑Aware LTR

This article reviews the development of Zhihu's search system, describing the transition from early GBDT ranking to deep neural networks, the introduction of multi‑objective and position‑bias‑aware learning‑to‑rank methods, context‑aware techniques, end‑to‑end training, personalization, and future research directions.

DNNGBDTdeep learning

0 likes · 17 min read

Evolution of Zhihu Search Ranking Models: From GBDT to DNN, Multi‑Goal and Context‑Aware LTR

Qunar Tech Salon

Aug 21, 2016 · Artificial Intelligence

Hotel Search Ranking: Problem Definition, Model Construction, Feature Engineering, and Offline Evaluation

This article presents a comprehensive overview of hotel search ranking, covering problem definition, the distinction between ranking and probability estimation, handling position bias, detailed feature engineering, the AnyBoost linear boosting model, offline evaluation methods, and observed online performance improvements.

Machine Learningfeature engineeringhotel ranking

0 likes · 7 min read