multi-objective

Qunar Tech Salon

Feb 17, 2025 · Artificial Intelligence

Evolution of Qunar Hotel Search Ranking: From LambdaMart to LambdaDNN and Multi‑Objective Optimization

The article details Qunar’s hotel search ranking system evolution, covering the shift from rule‑based sorting to LambdaMart, the adoption of LambdaDNN deep models, multi‑objective MMOE architectures, multi‑scenario integration, extensive feature engineering, and experimental results demonstrating significant offline and online performance gains.

Recommendation systemsdeep learningfeature selection

0 likes · 36 min read

Evolution of Qunar Hotel Search Ranking: From LambdaMart to LambdaDNN and Multi‑Objective Optimization

DataFunSummit

Feb 7, 2025 · Artificial Intelligence

Fusion Ranking and Multi-Objective Optimization in Recommendation Systems

This article introduces the role of ranking formulas in recommendation systems, compares sequence and value fusion methods, discusses multi‑objective trade‑offs, explains offline parameter search principles, and demonstrates the open‑source ParaDance framework for automated ranking formula optimization.

Recommendation systemsalgorithm engineeringmulti-objective

0 likes · 17 min read

Fusion Ranking and Multi-Objective Optimization in Recommendation Systems

JD Retail Technology

Dec 26, 2024 · Artificial Intelligence

Multi‑Objective Deep Reinforcement Learning Framework for E‑commerce Traffic Allocation (MODRL‑TA)

MODRL‑TA is a multi‑objective deep reinforcement learning framework that unites independent Q‑learning agents, a cross‑entropy‑based decision‑fusion module, and progressive data‑augmentation to overcome cold‑start and multi‑objective trade‑offs in e‑commerce traffic allocation, delivering up to 18% more impressions, 4% higher CTR and 5% higher CVR in live tests.

deep learninge-commercemulti-objective

0 likes · 14 min read

Multi‑Objective Deep Reinforcement Learning Framework for E‑commerce Traffic Allocation (MODRL‑TA)

Model Perspective

Oct 11, 2024 · Fundamentals

Beyond Maximizing: Exploring Diverse Decision‑Making Perspectives

This article examines how decision makers can move beyond a single "maximization" goal by considering satisficing, risk minimization, multi‑objective optimization, and regret minimization, offering a richer set of viewpoints for tackling complex, uncertain choices.

Optimizationdecision makingmulti-objective

0 likes · 10 min read

Beyond Maximizing: Exploring Diverse Decision‑Making Perspectives

Model Perspective

Sep 16, 2024 · Operations

Can 0‑1 Knapsack Modeling Turn You Into a Time‑Management Master?

This article applies 0‑1 knapsack and multi‑objective optimization models to illustrate how students and professionals can allocate limited daily hours among competing tasks, using weighted importance and urgency to devise optimal schedules illustrated with real‑world case studies.

0-1 knapsackOptimizationmulti-objective

0 likes · 7 min read

Can 0‑1 Knapsack Modeling Turn You Into a Time‑Management Master?

Model Perspective

May 29, 2022 · Operations

Designing an Optimization Model for Biodiversity Funding: Variables, Goals, Constraints

This article explains how to formulate and solve the 2020 B biodiversity funding problem as an optimization model, covering decision variables, objective functions, constraints, and common solution strategies such as multi‑objective conversion and algorithm selection.

Linear ProgrammingOptimizationbiodiversity

0 likes · 10 min read

Designing an Optimization Model for Biodiversity Funding: Variables, Goals, Constraints

DataFunSummit

Oct 31, 2021 · Artificial Intelligence

Exploring Generalized Multi‑Objective Recommendation Algorithms for 58 Community

This article details how 58 Community evolved its recommendation system from single‑objective click‑rate optimization to a multi‑objective framework that boosts value‑content share, improves user retention, and leverages cross‑domain embeddings and online CEM‑based parameter tuning to achieve significant performance gains.

CEMCross-Domainembedding

0 likes · 15 min read

Exploring Generalized Multi‑Objective Recommendation Algorithms for 58 Community

DataFunTalk

Jun 4, 2021 · Artificial Intelligence

Advances in Ranking Algorithms for the "Good Goods" Recommendation Scenario

This article presents a comprehensive overview of recent advancements in ranking algorithms for the Good Goods recommendation scenario, covering long‑sequence modeling, category‑retrieval attention, multi‑objective ranking, model structure optimizations, loss functions, and LTR techniques, along with experimental results and practical insights.

AttentionLTRRanking

0 likes · 13 min read

Advances in Ranking Algorithms for the "Good Goods" Recommendation Scenario

DataFunTalk

Oct 3, 2020 · Artificial Intelligence

MOBIUS: A Next‑Generation Multi‑Objective Recall System for Baidu Sponsored Search

This article introduces Baidu's new multi‑objective recall system (MOBIUS), which integrates relevance and business metrics such as CPM into the recall stage by migrating CTR models to recall, using data augmentation and a teacher‑student framework to improve ad monetization while preserving relevance.

Baiduadvertisingctr

0 likes · 10 min read

MOBIUS: A Next‑Generation Multi‑Objective Recall System for Baidu Sponsored Search

DataFunTalk

Sep 23, 2019 · Artificial Intelligence

Understanding UC International Feed Recommendation: Goal Determination, Multi‑Objective Estimation, and Mixed Ranking

This article explains how UC international feed recommendation tackles goal definition, multi‑objective point estimation using models such as ESMM, DBMTL and MMoE, mixed‑ranking optimization, and cold‑start challenges by leveraging content understanding and feature generalization to improve user satisfaction.

AICold StartRanking

0 likes · 12 min read