ranking model | BestHub

DataFunSummit

Mar 17, 2022 · Artificial Intelligence

Optimizing QQ Music Ranking Model: From User Perception to Multi‑Category Traffic Exploration

This talk presents the evolution of QQ Music's ranking system, detailing background challenges, user‑perception modeling, multi‑objective and causal learning to mitigate the Matthew effect, long‑tail content support, cross‑domain recommendation, and module personalization for diversified traffic, concluding with future research directions.

causal inferencecross-domain recommendationmulti-objective learning

0 likes · 16 min read

Optimizing QQ Music Ranking Model: From User Perception to Multi‑Category Traffic Exploration

DataFunTalk

Feb 14, 2022 · Artificial Intelligence

Optimizing QQ Music Ranking Models: From Pairwise Methods to Multi‑Objective Learning and Causal Inference

This talk details the evolution of QQ Music's ranking system, covering background, user‑perception modeling, pairwise optimization, advanced model architectures, multi‑objective learning with causal inference to mitigate the Matthew effect, cross‑domain recommendation, and module personalization that together boost user engagement and platform traffic.

causal inferencecross-domain recommendationmulti-objective learning

0 likes · 16 min read

Optimizing QQ Music Ranking Models: From Pairwise Methods to Multi‑Objective Learning and Causal Inference

DataFunTalk

Apr 25, 2019 · Artificial Intelligence

Comparison of Classification and Ranking Models in Recommendation Systems

This article examines the differences and similarities between classification (pointwise) and ranking (pairwise) models for recommendation systems, covering their probabilistic foundations, loss functions, parameter updates, and practical implications such as sensitivity to statistical features and robustness.

Machine LearningRecommendation systemsclassification model

0 likes · 10 min read

Comparison of Classification and Ranking Models in Recommendation Systems

HomeTech

Oct 29, 2018 · Artificial Intelligence

Applying ListNet Listwise Ranking Model for Car Purchase Intent Prediction

This article introduces the ListNet listwise ranking algorithm, explains its theoretical foundations and loss function, presents a Python implementation with gradient computation, and demonstrates its superior performance over pointwise and pairwise models on public benchmarks and an internal automotive dataset for predicting users' intended car series.

Machine LearningPythonlearning to rank

0 likes · 14 min read

Applying ListNet Listwise Ranking Model for Car Purchase Intent Prediction