Apple Inc.
PRIVATIZED APRIORI ALGORITHM FOR SEQUENTIAL DATA DISCOVERY

Abstract:

Embodiments described herein provide techniques to encode sequential data in a privacy preserving manner before the data is sent to a sequence learning server. The server can then determine aggregate trends within an overall set of users, without having any specific knowledge about the contributions of individual users. The server can be used to learn new words generated by user client devices in a crowdsourced manner while maintaining local differential privacy of client devices. The server can also learn other sequential data including typed, autocorrected, revised text sequences, sequences of application launches, sequences of purchases on an application store, or other sequences of activities that can be performed on an electronic device.