Deep Learning for Text Data on Mobile Devices

Abstract

With the rise of Artificial Intelligence (AI), it is becoming a significant phenomenon in our lives. As with many other powerful tools, AI brings many advantages but many risks as well. Predictions and automation can significantly help in our everyday lives. However, sending our data to servers for processing can severely hurt our privacy. In this paper, we describe experiments designed to find out whether we can enjoy the benefits of AI in the privacy of our mobile devices. We focus on text data since such data are easy to store in large quantities for mining by third parties. We measure the performance of deep learning methods in terms of accuracy (when compared to fully-fledged server models) and speed (number of text documents processed in a second). We conclude our paper with findings that with few relatively small modifications, mobile devices can process hundreds to thousands of documents while leveraging deep learning models.

Jako každá mocný nástroj, přináší spoustu výhod ale také spoustu risků. Predikce a automatizace může výrazně pomoci v našich každodenních životech. Odesílání uživatelských dat na server k procesování může narušit jejich soukromí. Soustředili jsme se na textová data a provedli několik experimentů, abychom ověřili, zda je odesílání dat na výpočetní servery nutností v době výkonných mobilních zařízeních.