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文章基本信息

  • 标题:Neural Scoring of Logical Inferences from Data using Feedback
  • 本地全文:下载
  • 作者:Allmin Susaiyah ; Aki Härmä ; Ehud Reiter
  • 期刊名称:International Journal of Interactive Multimedia and Artificial Intelligence
  • 印刷版ISSN:1989-1660
  • 出版年度:2021
  • 卷号:6
  • 期号:5
  • 页码:90-99
  • DOI:10.9781/ijimai.2021.02.004
  • 语种:English
  • 出版社:ImaI-Software
  • 摘要:Insights derived from wearable sensors in smartwatches or sleep trackers can help users in approaching their healthy lifestyle goals. These insights should indicate significant inferences from user behaviour and their generation should adapt automatically to the preferences and goals of the user. In this paper, we propose a neural network model that generates personalised lifestyle insights based on a model of their significance, and feedback from the user. Simulated analysis of our model shows its ability to assign high scores to a) insights with statistically significant behaviour patterns and b) topics related to simple or complex user preferences at any given time. We believe that the proposed neural networks model could be adapted for any application that needs user feedback to score logical inferences from data.
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