WWW
The Web Coferences
B) 2022
- On Designing a Two-stage Auction for Online Advertising
- Alleviating Cold-start Problem in CTR Prediction with A Variational Embedding Learning Framework
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paper review, implicit feedback, Recommendation System, WWW 17
B) Top Tier Conferences and Journals WWW, WSDM, SIGIR, KDD, RecSyS, CIKM, TOIS, TKDE, NIPS, ICML, AAAI, IUI, UMAP C) Companies
Personalizing Software and Web Services by Integrating Unstructured Application Usage Traces Tags paper review, implicit feedback, Recommendation System, WWW 17 paper link...
Must-read Papers on RS github.com/hongleizhang/RSPapers B) Top Tier Conferences and Journals WWW, WSDM, SIGIR, KDD, RecSyS, CIKM, TOIS, TKDE, NIPS, ICML, AAAI, IUI, UMAP C)...
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...
Variational Autoencoders for Collaborative Filtering With Mult-VAE, the authors introduce a generative model with multinomial likelihood, propose a different regularization...
Practical Lessons for Job Recommendations in the Cold-Start Scenario paper link Related References.
Neural Collaborative Filtering (WWW 2017) NeuMF unifies the strengths of MF and MLP in modeling user-item interactions.
Combating Selection Biases in Recommender Systems with a Few Unbiased Ratings Tags selection bias, Abstract Introduction unbiased ratings 포함시키는 방법: 임의로 선택된 일부 아이템들에 대해 유저들에게...
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...
Abstract 개인화 추천 및 ranking 방식을 진행할 때 아이템의 visual appearance 무시하는 경우가 많다.
CTR prediction 연구에서 공통된 평가 방식이나 표준화된 벤치마크가 부족하다. 다양한 모델들에 대하여 벤치마크를 진행하였고, 해당 결과나 진행한 코드는 reproducible 하도록 공개하였다.