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Zhihu Tech Column
Zhihu Tech Column
Jun 11, 2025 · Artificial Intelligence

How Minute‑Level Time Decay Boosts User Retention Modeling in Recommendation Systems

This article presents a novel minute‑level future‑reward framework with dual‑delay incentives, activity‑based attribution, multi‑task delayed modeling, and sequential streaming training that dramatically improves user retention prediction accuracy and real‑time performance in large‑scale recommendation platforms.

Deep Learningmulti‑task modelingreal‑time prediction
0 likes · 17 min read
How Minute‑Level Time Decay Boosts User Retention Modeling in Recommendation Systems
Top Architect
Top Architect
Jan 19, 2021 · Big Data

Designing a Content Hotness Scoring Algorithm for Community Platforms

This article describes how a community’s big‑data team designed a content hotness algorithm by defining time, interaction, content, and user dimensions, assigning business meanings, applying weighted formulas and a Newton‑cooling decay function, and integrating user interest vectors to compute dynamic scores.

Big Datacontent rankingengagement metrics
0 likes · 9 min read
Designing a Content Hotness Scoring Algorithm for Community Platforms
Xueersi Online School Tech Team
Xueersi Online School Tech Team
Jan 8, 2021 · Artificial Intelligence

Design and Implementation of a Rule‑Based and Collaborative‑Filtering Recommendation System for an Educational App

This article describes the business background, cold‑start challenges, rule‑based recall pipeline, Wilson interval and time‑decay scoring methods, item‑based collaborative filtering implementation with code, and experimental results that improved click‑through rates for the 学而思网校 educational application.

A/B-testCold StartWilson-interval
0 likes · 12 min read
Design and Implementation of a Rule‑Based and Collaborative‑Filtering Recommendation System for an Educational App