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Found 6 papers, 1 papers with code
What Are We Optimizing For? A Human-centric Evaluation Of Deep Learning-based Recommender Systems
Deep learning-based (DL) models in recommender systems (RecSys) have gained significant recognition for their remarkable accuracy in predicting user preferences.
Organizational Bulk Email Systems: Their Role and Performance in Remote Work
The COVID-19 pandemic has forced many employees to work from home.
Less Can Be More: Exploring Population Rating Dispositions with Partitioned Models in Recommender Systems
In this study, we partition users by rating disposition - looking first at their percentage of negative ratings, and then at the general use of the rating scale.
Getting the Most from Eye-Tracking: User-Interaction Based Reading Region Estimation Dataset and Models
A single digital newsletter usually contains many messages (regions).
HierCat: Hierarchical Query Categorization from Weakly Supervised Data at Facebook Marketplace
Query categorization at customer-to-customer e-commerce platforms like Facebook Marketplace is challenging due to the vagueness of search intent, noise in real-world data, and imbalanced training data across languages.
The Economics of Recommender Systems: Evidence from a Field Experiment on MovieLens
We conduct a field experiment on a movie-recommendation platform to identify if and how recommendations affect consumption.
