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Online learning to rank for information retrieval

Online learning to rank for information retrieval

2026년 6월 14일1 min read

Online Learning to Rank for Information Retrieval

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

함께 보면 좋은 글

Practical Lessons for Job Recommendations in the Cold-Start Scenario

Practical Lessons for Job Recommendations in the Cold-Start Scenario paper link Related References.

Collaborative Topic Modeling for Recommending GitHub Repositories

Collaborative Topic Modeling for Recommending GitHub Repositories Related References paper link: www.cs.cmu.edu/afs/cs.cmu.edu/Web/People/norii/pub/github-ctr.pdf .

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...

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

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...

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

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

Deep Neural Networks for YouTube Recommendations

paper link Abstract classic two-stage information retrieval dichotomy (2 단계 정보 검색 이분법) deep candidate generation model deep ranking model practical lessons and insights 을 제공...

VBPR - Visual Bayesian Personalized Ranking from Implicit Feedback

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

Reinforced Negative Sampling for Recommendation with Exposure Data

Introduction data (노출이 발생한 아이템) 정보는 유저들의 negative preference 에 대한 정보를 담고있지만 활용하기는 쉽지 않은데, 다음과 같은 이유가 있기 때문이다. 불완전성 노출된 아이템들은 일반적으로 추천 로직에 의해 선택된다.

Correcting for Selection Bias in Learning-to-rank Systems

Abstract selection bias, which occurs because clicked documents are reflective of what documents have been shown to the user in the first place.

A Survey on Deep Learning Based POI Recommendations

A Survey on Deep Learning Based POI Recommendations A POI recommendation technique essentially exploits users’ historical check-ins and other multimodal information to...

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