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Getting the Most from Eye-Tracking: User-Interaction Based Reading Region Estimation Dataset and Models.

, , , , , , and . ETRA, page 10:1-10:7. ACM, (2023)

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The Economics of Recommender Systems: Evidence from a Field Experiment on MovieLens., , , , and . EC, page 117. ACM, (2023)Learning to Ignore: A Case Study of Organization-Wide Bulk Email Effectiveness., , and . Proc. ACM Hum. Comput. Interact., 5 (CSCW1): 80:1-80:23 (2021)Organizational Bulk Email Systems: Their Role and Performance in Remote Work., , and . CoRR, (2023)Getting the Most from Eye-Tracking: User-Interaction Based Reading Region Estimation Dataset and Models., , , , , , and . ETRA, page 10:1-10:7. ACM, (2023)The Economics of Recommender Systems: Evidence from a Field Experiment on MovieLens., , , , and . CoRR, (2022)What Are We Optimizing For? A Human-centric Evaluation Of Deep Learning-based Recommender Systems., , , , and . CoRR, (2024)Interactive Content Diversity and User Exploration in Online Movie Recommenders: A Field Experiment., , , , and . CoRR, (2023)Group Preference Aggregation: A Nash Equilibrium Approach., , , , and . ICDM, page 679-688. IEEE Computer Society, (2016)Learning to Ignore: A Case Study of Organization-Wide Bulk Email Effectiveness., , and . CoRR, (2020)COVID-19 as Reflected in University President Bulk Email., , , , and . CoRR, (2024)