21 citations · 45 across the 11 of their papers we have counts for
Showing cs.IRShow all
3 papers · 1 filter
cs.IR2021★ 1 cited
Lessons Learned Addressing Dataset Bias in Model-Based Candidate Generation at Twitter
Alim Virani, Jay Baxter, Dan Shiebler +7
Traditionally, heuristic methods are used to generate candidates for large scale recommender systems. Model-based candidate generation promises multiple potential advantages, prima…
cs.IR2020★ 21 cited
Tuning Word2vec for Large Scale Recommendation Systems
Benjamin P. Chamberlain, Emanuele Rossi, Dan Shiebler +2
Word2vec is a powerful machine learning tool that emerged from Natural Lan-guage Processing (NLP) and is now applied in multiple domains, including recom-mender systems, forecastin…
cs.IR2018
A Correlation Maximization Approach for Cross Domain Co-Embeddings
Dan Shiebler
Although modern recommendation systems can exploit the structure in users' item feedback, most are powerless in the face of new users who provide no structure for them to exploit.…