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• W2893015217 abstract "Recent advances in spoken language technologies and the introduction of many customer facing products, have given rise to a wide customer reliance on smart personal assistants for many of their daily tasks. In this paper, we present a system to reduce users' cognitive load by extending personal assistants with long-term personal memory where users can store and retrieve by voice, arbitrary pieces of information. The problem is framed as a neural retrieval based question answering system where answers are selected from previously stored user memories. We propose to directly optimize the end-to-end retrieval performance, measured by the F1-score, using reinforcement learning, leading to better performance on our experimental test set(s)." @default.
• W2893015217 created "2018-10-05" @default.
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• W2893015217 date "2018-09-28" @default.
• W2893015217 modified "2023-09-27" @default.
• W2893015217 title "Direct optimization of F-measure for retrieval-based personal question answering" @default.
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• W2893015217 hasPublicationYear "2018" @default.
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