offline 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

58 Tech

Feb 24, 2022 · Artificial Intelligence

Deep Learning Ranking Model Enhancements for Recruitment Search at 58.com

This report details how the Search Recommendation team at 58.com upgraded their deep learning ranking model for recruitment by adding multi-valued and semantic vector features, integrating conversion sequences, employing feature‑crossing techniques, optimizing offline data pipelines, and planning future multi‑scene improvements to boost CTR and relevance.

AICTR predictionFeature Engineering

0 likes · 18 min read