minsoo9506 / RecSysBlog

추천시스템, 추천알고리즘 관련하여 공부하면서 블로그 형식으로 정리하는 곳

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  • 타인에게 설명한다고 생각하고 정리합니다.
  • 이를 기반으로 나중에 강의를 찍고 싶은 계획이 있습니다.

Index

  • Paper: 논문의 주요 내용을 정리합니다.
  • Industry: 회사들의 tech blog 주요 내용을 정리합니다.
  • Project: 추천시스템과 관련한 개인 프로젝트를 진행하면서 기록을 남기고 싶은 내용을 정리합니다.
  • Reference: 추천시스템과 관련한 정보를 아카이빙합니다.

📄 Paper

  • Factorization Machines, 2010
  • Wide & Deep Learning for Recommender Systems, 2016
  • Neural Collaborative Filtering, 2017
  • DeepFM: A Factorization-Machine based Neural Network for CTR Prediction, 2017
  • Real-time Personalization using Embeddings for Search Ranking at Airbnb, KDD 2018
  • Sampling-Bias-Corrected Neural Modeling for Large Corpus Item Recommendations, RecSys 2019
  • DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems 2020

🏢 Industry

Spotify

  • The Rise (and Lessons Learned) of ML Models to Personalize Content on Home, 2021
  • Introducing Natural Language Search for Podcast Episodes, 2022
  • Modeling Users According to Their Slow and Fast-Moving Interests, 2022

Pinterest

  • The machine learning behind delivering relevant ads, 2021
  • Pinterest Home Feed Unified Lightweight Scoring: A Two-tower Approach, 2021
  • Query Rewards: Building a Recommendation Feedback Loop During Query Selection, 2022
  • How Pinterest Leverages Realtime User Actions in Recommendation to Boost Homefeed Engagement Volume, 2022

Meta(Facebook)

  • How Instagram suggests new content, 2020

LinkedIn

  • The AI Behind LinkedIn Recruiter search and recommendation systems, 2019
  • Near real-time features for near real-time personalization, 2022
  • Community building recommender for group chats in LinkedIn Messaging, 2022

🧑🏻‍💻 Project

📑 Paper Reference

📑 Other Reference

About

추천시스템, 추천알고리즘 관련하여 공부하면서 블로그 형식으로 정리하는 곳