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The burden of organizing and scheduling time for tasks continues to reside with users of these systems, despite the high cognitive load associated with these activities. Users stand to benefit greatly from a task management system capable of prioritizing their pending tasks, thus saving them time and effort. In this article, we make three main contributions. First, we propose the problem of task prioritization, formulating it as a ranking over a user\u2019s pending tasks given a history of previous interactions with a task management system. Second, we perform an extensive analysis on the large-scale anonymized, de-identified logs of a popular task management application, deriving a dataset of grounded, real-world tasks from which to learn and evaluate our proposed system. We also identify patterns in how people record tasks as complete, which vary consistently with the nature of the task. Third, we propose a novel contextual deep learning solution capable of performing personalized task prioritization. In a battery of tests, we show that this approach outperforms several operational baselines and other sequential ranking models from previous work. Our findings have implications for understanding the ways people prioritize and manage tasks with digital tools, and in the design of support for users of task management applications.<\/jats:p>","DOI":"10.1145\/3486861","type":"journal-article","created":{"date-parts":[[2021,12,8]],"date-time":"2021-12-08T20:11:53Z","timestamp":1638994313000},"page":"1-28","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Grounded Task Prioritization with Context-Aware Sequential Ranking"],"prefix":"10.1145","volume":"40","author":[{"given":"Chuxu","family":"Zhang","sequence":"first","affiliation":[{"name":"Brandeis University, Waltham, MA"}]},{"given":"Julia","family":"Kiseleva","sequence":"additional","affiliation":[{"name":"Microsoft Research, Redmond, WA"}]},{"given":"Sujay Kumar","family":"Jauhar","sequence":"additional","affiliation":[{"name":"Microsoft Research, Redmond, WA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0265-4249","authenticated-orcid":false,"given":"Ryen W.","family":"White","sequence":"additional","affiliation":[{"name":"Microsoft Research, Redmond, WA"}]}],"member":"320","published-online":{"date-parts":[[2021,12,8]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1145\/2976749.2978318"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-85820-3_7"},{"key":"e_1_3_2_4_2","volume-title":"Getting Things Done: The Art of Stress-free Productivity","author":"Allen David","year":"2015","unstructured":"David Allen. 2015. 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