Neural Scoring of Logical Inferences from Data using Feedback

Insights derived from wearable sensors in smartwatches or sleep trackers can help users approaching their healthy lifestyle goals. These insights should indicate significant inferences user behaviour and generation adapt automatically to the preferences goals of user. In this paper, we propose a neural network model that generates personalised based on significance, feedback Simulated analysis our shows its ability assign high scores a) with statistically patterns b) topics related simple complex at any given time. We believe proposed networks could be adapted for application needs score logical data.