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Online learning to rank for information retrieval

Online learning to rank for information retrieval

2026년 8월 29일1 min read

References

  • slide: https://staff.fnwi.uva.nl/m.derijke/wp-content/uploads/sigir2016-tutorial.pdf

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Interactively Optimizing Information Retrieval Systems as a Dueling Bandits Problem

Related papers/recommender_system/Online learning to rank for information retrieval Multileave Gradient Descent

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Practical Lessons for Job Recommendations in the Cold-Start Scenario

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Interactively Optimizing Information Retrieval Systems as a Dueling Bandits Problem

Dueling Bandit Gradient Descent Related papers/recommender system/Online learning to rank for information retrieval Multileave Gradient Descent.

Wide & Deep Learning for Recommender Systems

Introduction A wide linear model and a deep neural network are trained together to both memorize and generalize a recommendation systems.

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

Paper link Abstract 사용자와 이벤트를 동일한 latent space 에 project 하기 위해 a joint representation model (결합 표현 모델) 을 제안 제안한 모델은 parallel CNN 기반이고, event text 의 semantic meaning 을 파악하며...

Collaborative Topic Modeling for Recommending GitHub Repositories

References paper link: www.cs.cmu.edu/afs/cs.cmu.edu/Web/People/norii/pub/github-ctr.pdf .

User Fatigue in Online News Recommendation

Abstract the impact of User Fatigue has been mostly ignored in the literature User fatigue 란, 특정 유저에게 동일한 아이템을 반복적으로 보여줬을 때, 해당 아이템에 대해 빠르게 흥미를 잃는 현상을 의미한다.

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

Abstract NLP 에서 dual encoder 로 불리는 two-tower 신경망 framework 를 어떻게 추천 시스템에 적용할 수 있는지 보임 추가로, Mixed Negative Sampling (MNS) 이라는 negative sampling 전략을 제안 일반적인 batch 또는 unigram...

Improving Pairwise Learning for Item Recommendation from Implicit Feedback

Abstract Pairwise 알고리즘 학습에서 사용하는 SGD (with uniformly drawn pairs) 방식은 아이템의 인기 정도가 tailed 분포를 따른다면 학습이 매우 느려진다는 점을 보임 이러한 문제를 극복하기 위해서 non-uniform item sampler 를 제안 해당 sampler...

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

Paper link www.pelleg.org/shared/hp/download/relevance-is-not-enough.pdf 배경 question-answering sites 에 대한 추천 시스템 The feature that they really missed was diversity.

VBPR - Visual Bayesian Personalized Ranking from Implicit Feedback

Abstract 개인화 추천 및 ranking 방식을 진행할 때 아이템의 visual appearance 무시하는 경우가 많다.