Automated Extraction of Personal Knowledge from Smartphone Push Notifications

TL;DR

This paper presents an automated method to extract personal knowledge from smartphone push notifications by discovering templates and understanding their semantics, enabling accurate knowledge extraction while preserving user privacy.

Contribution

It introduces a novel automated approach combining pattern mining and machine learning to extract personal knowledge from notifications without requiring predefined templates.

Findings

High accuracy in knowledge extraction from 120 million notifications

Efficient processing suitable for large-scale deployment

Preserves user privacy by only uploading templates, not personal data

Abstract

Personalized services are in need of a rich and powerful personal knowledge base, i.e. a knowledge base containing information about the user. This paper proposes an approach to extracting personal knowledge from smartphone push notifications, which are used by mobile systems and apps to inform users of a rich range of information. Our solution is based on the insight that most notifications are formatted using templates, while knowledge entities can be usually found within the parameters to the templates. As defining all the notification templates and their semantic rules are impractical due to the huge number of notification templates used by potentially millions of apps, we propose an automated approach for personal knowledge extraction from push notifications. We first discover notification templates through pattern mining, then use machine learning to understand the template semantics. Based on the templates and their semantics, we are able to translate notification text into knowledge facts automatically. Users' privacy is preserved as we only need to upload the templates to the server for model training, which do not contain any personal information. According to our experiments with about 120 million push notifications from 100,000 smartphone users, our system is able to extract personal knowledge accurately and efficiently.