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6 papers · 2 filters
Extracting Entities of Interest from Comparative Product Reviews
Jatin Arora, Sumit Agrawal, Pawan Goyal +1
This paper presents a deep learning based approach to extract product comparison information out of user reviews on various e-commerce websites. Any comparative product review has…
Stationary Algorithmic Balancing For Dynamic Email Re-Ranking Problem
Jiayi Liu, Jennifer Neville
Email platforms need to generate personalized rankings of emails that satisfy user preferences, which may vary over time. We approach this as a recommendation problem based on thre…
Auditing Cross-Cultural Consistency of Human-Annotated Labels for Recommendation Systems
Rock Yuren Pang, Jack Cenatempo, Franklyn Graham +5
Recommendation systems increasingly depend on massive human-labeled datasets; however, the human annotators hired to generate these labels increasingly come from homogeneous backgr…
Unsupervised Dense Retrieval Training with Web Anchors
Yiqing Xie, Xiao Liu, Chenyan Xiong
In this work, we present an unsupervised retrieval method with contrastive learning on web anchors. The anchor text describes the content that is referenced from the linked page. T…
Towards Explainable Collaborative Filtering with Taste Clusters Learning
Yuntao Du, Jianxun Lian, Jing Yao +5
Collaborative Filtering (CF) is a widely used and effective technique for recommender systems. In recent decades, there have been significant advancements in latent embedding-based…
Patterns of gender-specializing query reformulation
Amifa Raj, Bhaskar Mitra, Nick Craswell +1
Users of search systems often reformulate their queries by adding query terms to reflect their evolving information need or to more precisely express their information need when th…