Recommender System

Zzong's Notes

검색과 추천 모델을 만드는 머신러닝 엔지니어가 일하고 공부하며 정리한 노트입니다. 개념 설명, 논문 읽은 기록, 직접 해 본 실험을 한곳에 모았습니다. 쓴 사람이 궁금하다면 이력서를 보세요. 처음이라면 여기부터 검색이 궁금하다면 검색 노트 안내 단어로 찾는 방법과 뜻으로 찾는 방법이 어떻게 다른지부터 짚고, 나머지 검색 노트로 이어 줍니다. LLM 학습이 궁금하다면 자연스러운 한국어를 위한 ...

Zzong's Notes

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Recommender System

A Survey on Deep Learning Based POI Recommendations

Algorithmic Effects on the Diversity of Consumption on Spotify

AliBoost - Ecological Boosting Framework in Alibaba Platform

An Empirical Study on Recommendation with Multiple Types of Feedback

An Improved Sampler for Bayesian Personalized Ranking by Leveraging View Data

BERT4Rec - Sequential Recommendation with Bidirectional Encoder Representations from Transformer

Beyond Collaborative Filtering - The List Recommendation Problem

Collaborative Topic Modeling for Recommending GitHub Repositories

Deep Neural Networks for YouTube Recommendations

DeepFM - A Factorization-Machine based Neural Network for CTR Prediction

Effects of User Negative Experience in Mobile News Streaming

Fifty Shades of Ratings - How to Benefit from a Negative Feedback in Top-N Recommendations Tasks

Improving Pairwise Learning for Item Recommendation from Implicit Feedback

Interpreting user inaction in recommender systems

Joint User-Entity Representation Learning for Event Recommendation in Social Network

Learning to Rank Recommendations with the k-Order Statistic Loss

Mixed Negative Sampling for Learning Two-tower Neural Networks in Recommendations

Modeling impression discounting in large-scale recommender systems

Modeling personalized item frequency information for next-basket recommendation

MOON - Generative MLLM-based Multimodal Representation Learning for E-commerce Product Understanding

Negative Interactions for Improved Collaborative Filtering - Don't go Deeper, go Higher

Online learning to rank for information retrieval

Personalizing Software and Web Services by Integrating Unstructured Application Usage Traces

Practical Lessons for Job Recommendations in the Cold-Start Scenario

Progressive Alignment of Recommender Foundation Model through Multi-Phase Post-Training

Recommending Podcasts for Cold-Start Users Based on Music Listening and Taste

Reinforced Negative Sampling for Recommendation with Exposure Data

session-based recommendations

SLIM - Sparse Linear Methods for Top-N Recommender Systems

The YouTube Video Recommendation System

User Fatigue in Online News Recommendation

VBPR - Visual Bayesian Personalized Ranking from Implicit Feedback

When Relevance is not Enough - Promoting Diversity and Freshness in Personalized Question Recommendation

Wide & Deep Learning for Recommender Systems

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