Zzong's Notes

Home

❯

papers

❯

recommender_system

❯

Collaborative Topic Modeling for Recommending GitHub Repositories

Collaborative Topic Modeling for Recommending GitHub Repositories

2026년 8월 29일1 min read

References

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

링크된 언급

1
Collaborative Topic Regression

Collaborative Topic Modeling for Recommending GitHub Repositories Collaborative Topic Modeling for Recommending Scientific Articles

함께 보면 좋은 글

Collaborative Topic Regression

collaborative filtering 과 topic modeling 을 합친 모델을 의미 Approaches naive r {ij}\sim\mathcal{N}\left(u {i}^{T}\theta {j},c {ij}^{-1}\right) The Generative Process for CTR 각 사용자 i...

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...

Practical Lessons for Job Recommendations in the Cold-Start Scenario

paper link .

VBPR - Visual Bayesian Personalized Ranking from Implicit Feedback

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

Online learning to rank for information retrieval

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

A Survey on Deep Learning Based POI Recommendations

A POI recommendation technique essentially exploits users’ historical check-ins and other multimodal information to recommend the next set of POIs suitable for a user.

Modeling personalized item frequency information for next-basket recommendation

Abstract SBRS 에서 Next-basket 추천 (NBR) 을 위해 제안된 논문이다. RNN 모델이 sequential modeling 에 효과적이지만 추천 시나리오에서 item frequency 정보를 직접적으로 잡아낼 수 없다는 문제가 있다고 주장한다.

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...

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.

Neural Collaborative Filtering (WWW 2017)

NeuMF unifies the strengths of MF and MLP in modeling user-item interactions.