Neural Scoring of Logical Inferences from Data using Feedback

Author
Keywords
Abstract
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.
Year of Publication
2021
Journal
International Journal of Interactive Multimedia and Artificial Intelligence
Volume
6
Issue
Special Issue on Artificial Intelligence, Paving the Way to the Future
Number
5
Number of Pages
90-99
Date Published
03/2021
ISSN Number
1989-1660
URL
https://www.ijimai.org/journal/sites/default/files/2021-03/ijimai_6_5_9.pdf
DOI
10.9781/ijimai.2021.02.004
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